On the functional integral approach in quantum statistics. 1. Some approximations
International Nuclear Information System (INIS)
Dai Xianxi.
1990-08-01
In this paper the susceptibility of a Kondo system in a fairly wide temperature region is calculated in the first harmonic approximation in a functional integral approach. The comparison with that of the renormalization group theory shows that in this region the two results agree quite well. The expansion of the partition function with infinite independent harmonics for the Anderson model is studied. Some symmetry relations are generalized. It is a challenging problem to develop a functional integral approach including diagram analysis, mixed mode effects and some exact relations in the Anderson system proved in the functional integral approach. These topics will be discussed in the next paper. (author). 22 refs, 1 fig
Salajegheh, Maral; Nejad, S. Mohammad Moosavi; Khanpour, Hamzeh; Tehrani, S. Atashbar
2018-05-01
In this paper, we present SMKA18 analysis, which is a first attempt to extract the set of next-to-next-leading-order (NNLO) spin-dependent parton distribution functions (spin-dependent PDFs) and their uncertainties determined through the Laplace transform technique and Jacobi polynomial approach. Using the Laplace transformations, we present an analytical solution for the spin-dependent Dokshitzer-Gribov-Lipatov-Altarelli-Parisi evolution equations at NNLO approximation. The results are extracted using a wide range of proton g1p(x ,Q2) , neutron g1n(x ,Q2) , and deuteron g1d(x ,Q2) spin-dependent structure functions data set including the most recent high-precision measurements from COMPASS16 experiments at CERN, which are playing an increasingly important role in global spin-dependent fits. The careful estimations of uncertainties have been done using the standard Hessian error propagation. We will compare our results with the available spin-dependent inclusive deep inelastic scattering data set and other results for the spin-dependent PDFs in literature. The results obtained for the spin-dependent PDFs as well as spin-dependent structure functions are clearly explained both in the small and large values of x .
International Nuclear Information System (INIS)
Lorenzana, J.; Grynberg, M.D.; Yu, L.; Yonemitsu, K.; Bishop, A.R.
1992-11-01
The ground state energy, and static and dynamic correlation functions are investigated in the inhomogeneous Hartree-Fock (HF) plus random phase approximation (RPA) approach applied to a one-dimensional spinless fermion model showing self-trapped doping states at the mean field level. Results are compared with homogeneous HF and exact diagonalization. RPA fluctuations added to the generally inhomogeneous HF ground state allows the computation of dynamical correlation functions that compare well with exact diagonalization results. The RPA correction to the ground state energy agrees well with the exact results at strong and weak coupling limits. We also compare it with a related quasi-boson approach. The instability towards self-trapped behaviour is signaled by a RPA mode with frequency approaching zero. (author). 21 refs, 10 figs
Tamosiunaite, Minija; Asfour, Tamim; Wörgötter, Florentin
2009-03-01
Reinforcement learning methods can be used in robotics applications especially for specific target-oriented problems, for example the reward-based recalibration of goal directed actions. To this end still relatively large and continuous state-action spaces need to be efficiently handled. The goal of this paper is, thus, to develop a novel, rather simple method which uses reinforcement learning with function approximation in conjunction with different reward-strategies for solving such problems. For the testing of our method, we use a four degree-of-freedom reaching problem in 3D-space simulated by a two-joint robot arm system with two DOF each. Function approximation is based on 4D, overlapping kernels (receptive fields) and the state-action space contains about 10,000 of these. Different types of reward structures are being compared, for example, reward-on- touching-only against reward-on-approach. Furthermore, forbidden joint configurations are punished. A continuous action space is used. In spite of a rather large number of states and the continuous action space these reward/punishment strategies allow the system to find a good solution usually within about 20 trials. The efficiency of our method demonstrated in this test scenario suggests that it might be possible to use it on a real robot for problems where mixed rewards can be defined in situations where other types of learning might be difficult.
Smooth function approximation using neural networks.
Ferrari, Silvia; Stengel, Robert F
2005-01-01
An algebraic approach for representing multidimensional nonlinear functions by feedforward neural networks is presented. In this paper, the approach is implemented for the approximation of smooth batch data containing the function's input, output, and possibly, gradient information. The training set is associated to the network adjustable parameters by nonlinear weight equations. The cascade structure of these equations reveals that they can be treated as sets of linear systems. Hence, the training process and the network approximation properties can be investigated via linear algebra. Four algorithms are developed to achieve exact or approximate matching of input-output and/or gradient-based training sets. Their application to the design of forward and feedback neurocontrollers shows that algebraic training is characterized by faster execution speeds and better generalization properties than contemporary optimization techniques.
Measure Fields for Function Approximation
1993-06-01
intelligence research is provided by ONR contract N00014-91-J-4038 J.L. Marroquin was supported in part by a grant from the Consejo Nacional de Ciencia y ... Tecnologia , Mexico. _ 93-28011 9-3 -- -" nnuM IInu 4 0 0 0 1 Introduction imating functions are always discontinuous, and the dis- continuities are...capacity and generalization capabili- is present panel (a) of figure 1 shows a function z(z, y ) ties. that is equal to a tilted plane inside an L
A unified approach to the Darwin approximation
International Nuclear Information System (INIS)
Krause, Todd B.; Apte, A.; Morrison, P. J.
2007-01-01
There are two basic approaches to the Darwin approximation. The first involves solving the Maxwell equations in Coulomb gauge and then approximating the vector potential to remove retardation effects. The second approach approximates the Coulomb gauge equations themselves, then solves these exactly for the vector potential. There is no a priori reason that these should result in the same approximation. Here, the equivalence of these two approaches is investigated and a unified framework is provided in which to view the Darwin approximation. Darwin's original treatment is variational in nature, but subsequent applications of his ideas in the context of Vlasov's theory are not. We present here action principles for the Darwin approximation in the Vlasov context, and this serves as a consistency check on the use of the approximation in this setting
Random phase approximation in relativistic approach
International Nuclear Information System (INIS)
Ma Zhongyu; Yang Ding; Tian Yuan; Cao Ligang
2009-01-01
Some special issues of the random phase approximation(RPA) in the relativistic approach are reviewed. A full consistency and proper treatment of coupling to the continuum are responsible for the successful application of the RPA in the description of dynamical properties of finite nuclei. The fully consistent relativistic RPA(RRPA) requires that the relativistic mean filed (RMF) wave function of the nucleus and the RRPA correlations are calculated in a same effective Lagrangian and the consistent treatment of the Dirac sea of negative energy states. The proper treatment of the single particle continuum with scattering asymptotic conditions in the RMF and RRPA is discussed. The full continuum spectrum can be described by the single particle Green's function and the relativistic continuum RPA is established. A separable form of the paring force is introduced in the relativistic quasi-particle RPA. (authors)
An approximate analytical approach to resampling averages
DEFF Research Database (Denmark)
Malzahn, Dorthe; Opper, M.
2004-01-01
Using a novel reformulation, we develop a framework to compute approximate resampling data averages analytically. The method avoids multiple retraining of statistical models on the samples. Our approach uses a combination of the replica "trick" of statistical physics and the TAP approach for appr...... for approximate Bayesian inference. We demonstrate our approach on regression with Gaussian processes. A comparison with averages obtained by Monte-Carlo sampling shows that our method achieves good accuracy....
Cendagorta, Joseph R; Bačić, Zlatko; Tuckerman, Mark E
2018-03-14
We introduce a scheme for approximating quantum time correlation functions numerically within the Feynman path integral formulation. Starting with the symmetrized version of the correlation function expressed as a discretized path integral, we introduce a change of integration variables often used in the derivation of trajectory-based semiclassical methods. In particular, we transform to sum and difference variables between forward and backward complex-time propagation paths. Once the transformation is performed, the potential energy is expanded in powers of the difference variables, which allows us to perform the integrals over these variables analytically. The manner in which this procedure is carried out results in an open-chain path integral (in the remaining sum variables) with a modified potential that is evaluated using imaginary-time path-integral sampling rather than requiring the generation of a large ensemble of trajectories. Consequently, any number of path integral sampling schemes can be employed to compute the remaining path integral, including Monte Carlo, path-integral molecular dynamics, or enhanced path-integral molecular dynamics. We believe that this approach constitutes a different perspective in semiclassical-type approximations to quantum time correlation functions. Importantly, we argue that our approximation can be systematically improved within a cumulant expansion formalism. We test this approximation on a set of one-dimensional problems that are commonly used to benchmark approximate quantum dynamical schemes. We show that the method is at least as accurate as the popular ring-polymer molecular dynamics technique and linearized semiclassical initial value representation for correlation functions of linear operators in most of these examples and improves the accuracy of correlation functions of nonlinear operators.
Cendagorta, Joseph R.; Bačić, Zlatko; Tuckerman, Mark E.
2018-03-01
We introduce a scheme for approximating quantum time correlation functions numerically within the Feynman path integral formulation. Starting with the symmetrized version of the correlation function expressed as a discretized path integral, we introduce a change of integration variables often used in the derivation of trajectory-based semiclassical methods. In particular, we transform to sum and difference variables between forward and backward complex-time propagation paths. Once the transformation is performed, the potential energy is expanded in powers of the difference variables, which allows us to perform the integrals over these variables analytically. The manner in which this procedure is carried out results in an open-chain path integral (in the remaining sum variables) with a modified potential that is evaluated using imaginary-time path-integral sampling rather than requiring the generation of a large ensemble of trajectories. Consequently, any number of path integral sampling schemes can be employed to compute the remaining path integral, including Monte Carlo, path-integral molecular dynamics, or enhanced path-integral molecular dynamics. We believe that this approach constitutes a different perspective in semiclassical-type approximations to quantum time correlation functions. Importantly, we argue that our approximation can be systematically improved within a cumulant expansion formalism. We test this approximation on a set of one-dimensional problems that are commonly used to benchmark approximate quantum dynamical schemes. We show that the method is at least as accurate as the popular ring-polymer molecular dynamics technique and linearized semiclassical initial value representation for correlation functions of linear operators in most of these examples and improves the accuracy of correlation functions of nonlinear operators.
An Approximate Approach to Automatic Kernel Selection.
Ding, Lizhong; Liao, Shizhong
2016-02-02
Kernel selection is a fundamental problem of kernel-based learning algorithms. In this paper, we propose an approximate approach to automatic kernel selection for regression from the perspective of kernel matrix approximation. We first introduce multilevel circulant matrices into automatic kernel selection, and develop two approximate kernel selection algorithms by exploiting the computational virtues of multilevel circulant matrices. The complexity of the proposed algorithms is quasi-linear in the number of data points. Then, we prove an approximation error bound to measure the effect of the approximation in kernel matrices by multilevel circulant matrices on the hypothesis and further show that the approximate hypothesis produced with multilevel circulant matrices converges to the accurate hypothesis produced with kernel matrices. Experimental evaluations on benchmark datasets demonstrate the effectiveness of approximate kernel selection.
Nonlinear Ritz approximation for Fredholm functionals
Directory of Open Access Journals (Sweden)
Mudhir A. Abdul Hussain
2015-11-01
Full Text Available In this article we use the modify Lyapunov-Schmidt reduction to find nonlinear Ritz approximation for a Fredholm functional. This functional corresponds to a nonlinear Fredholm operator defined by a nonlinear fourth-order differential equation.
Energy Technology Data Exchange (ETDEWEB)
Rüger, Robert, E-mail: rueger@scm.com [Scientific Computing & Modelling NV, De Boelelaan 1083, 1081 HV Amsterdam (Netherlands); Department of Theoretical Chemistry, Vrije Universiteit Amsterdam, De Boelelaan 1083, 1081 HV Amsterdam (Netherlands); Wilhelm-Ostwald-Institut für Physikalische und Theoretische Chemie, Linnéstr. 2, 04103 Leipzig (Germany); Lenthe, Erik van [Scientific Computing & Modelling NV, De Boelelaan 1083, 1081 HV Amsterdam (Netherlands); Heine, Thomas [Wilhelm-Ostwald-Institut für Physikalische und Theoretische Chemie, Linnéstr. 2, 04103 Leipzig (Germany); Visscher, Lucas [Department of Theoretical Chemistry, Vrije Universiteit Amsterdam, De Boelelaan 1083, 1081 HV Amsterdam (Netherlands)
2016-05-14
We propose a new method of calculating electronically excited states that combines a density functional theory based ground state calculation with a linear response treatment that employs approximations used in the time-dependent density functional based tight binding (TD-DFTB) approach. The new method termed time-dependent density functional theory TD-DFT+TB does not rely on the DFTB parametrization and is therefore applicable to systems involving all combinations of elements. We show that the new method yields UV/Vis absorption spectra that are in excellent agreement with computationally much more expensive TD-DFT calculations. Errors in vertical excitation energies are reduced by a factor of two compared to TD-DFTB.
Polynomial approximation of functions in Sobolev spaces
International Nuclear Information System (INIS)
Dupont, T.; Scott, R.
1980-01-01
Constructive proofs and several generalizations of approximation results of J. H. Bramble and S. R. Hilbert are presented. Using an averaged Taylor series, we represent a function as a polynomical plus a remainder. The remainder can be manipulated in many ways to give different types of bounds. Approximation of functions in fractional order Sobolev spaces is treated as well as the usual integer order spaces and several nonstandard Sobolev-like spaces
Semiclassical initial value approximation for Green's function.
Kay, Kenneth G
2010-06-28
A semiclassical initial value approximation is obtained for the energy-dependent Green's function. For a system with f degrees of freedom the Green's function expression has the form of a (2f-1)-dimensional integral over points on the energy surface and an integral over time along classical trajectories initiated from these points. This approximation is derived by requiring an integral ansatz for Green's function to reduce to Gutzwiller's semiclassical formula when the integrations are performed by the stationary phase method. A simpler approximation is also derived involving only an (f-1)-dimensional integral over momentum variables on a Poincare surface and an integral over time. The relationship between the present expressions and an earlier initial value approximation for energy eigenfunctions is explored. Numerical tests for two-dimensional systems indicate that good accuracy can be obtained from the initial value Green's function for calculations of autocorrelation spectra and time-independent wave functions. The relative advantages of initial value approximations for the energy-dependent Green's function and the time-dependent propagator are discussed.
RATIONAL APPROXIMATIONS TO GENERALIZED HYPERGEOMETRIC FUNCTIONS.
Under weak restrictions on the various free parameters, general theorems for rational representations of the generalized hypergeometric functions...and certain Meijer G-functions are developed. Upon specialization, these theorems yield a sequency of rational approximations which converge to the
Multidimensional stochastic approximation using locally contractive functions
Lawton, W. M.
1975-01-01
A Robbins-Monro type multidimensional stochastic approximation algorithm which converges in mean square and with probability one to the fixed point of a locally contractive regression function is developed. The algorithm is applied to obtain maximum likelihood estimates of the parameters for a mixture of multivariate normal distributions.
On approximation of functions by product operators
Directory of Open Access Journals (Sweden)
Hare Krishna Nigam
2013-12-01
Full Text Available In the present paper, two quite new reults on the degree of approximation of a function f belonging to the class Lip(α,r, 1≤ r <∞ and the weighted class W(Lr,ξ(t, 1≤ r <∞ by (C,2(E,1 product operators have been obtained. The results obtained in the present paper generalize various known results on single operators.
Function approximation of tasks by neural networks
International Nuclear Information System (INIS)
Gougam, L.A.; Chikhi, A.; Mekideche-Chafa, F.
2008-01-01
For several years now, neural network models have enjoyed wide popularity, being applied to problems of regression, classification and time series analysis. Neural networks have been recently seen as attractive tools for developing efficient solutions for many real world problems in function approximation. The latter is a very important task in environments where computation has to be based on extracting information from data samples in real world processes. In a previous contribution, we have used a well known simplified architecture to show that it provides a reasonably efficient, practical and robust, multi-frequency analysis. We have investigated the universal approximation theory of neural networks whose transfer functions are: sigmoid (because of biological relevance), Gaussian and two specified families of wavelets. The latter have been found to be more appropriate to use. The aim of the present contribution is therefore to use a m exican hat wavelet a s transfer function to approximate different tasks relevant and inherent to various applications in physics. The results complement and provide new insights into previously published results on this problem
Ziegler, Tom; Krykunov, Mykhaylo; Autschbach, Jochen
2014-09-09
The random phase approximation (RPA) equation of adiabatic time dependent density functional ground state response theory (ATDDFT) has been used extensively in studies of excited states. It extracts information about excited states from frequency dependent ground state response properties and avoids, thus, in an elegant way, direct Kohn-Sham calculations on excited states in accordance with the status of DFT as a ground state theory. Thus, excitation energies can be found as resonance poles of frequency dependent ground state polarizability from the eigenvalues of the RPA equation. ATDDFT is approximate in that it makes use of a frequency independent energy kernel derived from the ground state functional. It is shown in this study that one can derive the RPA equation of ATDDFT from a purely variational approach in which stationary states above the ground state are located using our constricted variational DFT (CV-DFT) method and the ground state functional. Thus, locating stationary states above the ground state due to one-electron excitations with a ground state functional is completely equivalent to solving the RPA equation of TDDFT employing the same functional. The present study is an extension of a previous work in which we demonstrated the equivalence between ATDDFT and CV-DFT within the Tamm-Dancoff approximation.
When Density Functional Approximations Meet Iron Oxides.
Meng, Yu; Liu, Xing-Wu; Huo, Chun-Fang; Guo, Wen-Ping; Cao, Dong-Bo; Peng, Qing; Dearden, Albert; Gonze, Xavier; Yang, Yong; Wang, Jianguo; Jiao, Haijun; Li, Yongwang; Wen, Xiao-Dong
2016-10-11
Three density functional approximations (DFAs), PBE, PBE+U, and Heyd-Scuseria-Ernzerhof screened hybrid functional (HSE), were employed to investigate the geometric, electronic, magnetic, and thermodynamic properties of four iron oxides, namely, α-FeOOH, α-Fe 2 O 3 , Fe 3 O 4 , and FeO. Comparing our calculated results with available experimental data, we found that HSE (a = 0.15) (containing 15% "screened" Hartree-Fock exchange) can provide reliable values of lattice constants, Fe magnetic moments, band gaps, and formation energies of all four iron oxides, while standard HSE (a = 0.25) seriously overestimates the band gaps and formation energies. For PBE+U, a suitable U value can give quite good results for the electronic properties of each iron oxide, but it is challenging to accurately get other properties of the four iron oxides using the same U value. Subsequently, we calculated the Gibbs free energies of transformation reactions among iron oxides using the HSE (a = 0.15) functional and plotted the equilibrium phase diagrams of the iron oxide system under various conditions, which provide reliable theoretical insight into the phase transformations of iron oxides.
Discovery of functional and approximate functional dependencies in relational databases
Directory of Open Access Journals (Sweden)
Ronald S. King
2003-01-01
Full Text Available This study develops the foundation for a simple, yet efficient method for uncovering functional and approximate functional dependencies in relational databases. The technique is based upon the mathematical theory of partitions defined over a relation's row identifiers. Using a levelwise algorithm the minimal non-trivial functional dependencies can be found using computations conducted on integers. Therefore, the required operations on partitions are both simple and fast. Additionally, the row identifiers provide the added advantage of nominally identifying the exceptions to approximate functional dependencies, which can be used effectively in practical data mining applications.
Approximation of Analytic Functions by Bessel's Functions of Fractional Order
Directory of Open Access Journals (Sweden)
Soon-Mo Jung
2011-01-01
Full Text Available We will solve the inhomogeneous Bessel's differential equation x2y″(x+xy′(x+(x2-ν2y(x=∑m=0∞amxm, where ν is a positive nonintegral number and apply this result for approximating analytic functions of a special type by the Bessel functions of fractional order.
Function approximation with polynomial regression slines
International Nuclear Information System (INIS)
Urbanski, P.
1996-01-01
Principles of the polynomial regression splines as well as algorithms and programs for their computation are presented. The programs prepared using software package MATLAB are generally intended for approximation of the X-ray spectra and can be applied in the multivariate calibration of radiometric gauges. (author)
A partition function approximation using elementary symmetric functions.
Directory of Open Access Journals (Sweden)
Ramu Anandakrishnan
Full Text Available In statistical mechanics, the canonical partition function [Formula: see text] can be used to compute equilibrium properties of a physical system. Calculating [Formula: see text] however, is in general computationally intractable, since the computation scales exponentially with the number of particles [Formula: see text] in the system. A commonly used method for approximating equilibrium properties, is the Monte Carlo (MC method. For some problems the MC method converges slowly, requiring a very large number of MC steps. For such problems the computational cost of the Monte Carlo method can be prohibitive. Presented here is a deterministic algorithm - the direct interaction algorithm (DIA - for approximating the canonical partition function [Formula: see text] in [Formula: see text] operations. The DIA approximates the partition function as a combinatorial sum of products known as elementary symmetric functions (ESFs, which can be computed in [Formula: see text] operations. The DIA was used to compute equilibrium properties for the isotropic 2D Ising model, and the accuracy of the DIA was compared to that of the basic Metropolis Monte Carlo method. Our results show that the DIA may be a practical alternative for some problems where the Monte Carlo method converge slowly, and computational speed is a critical constraint, such as for very large systems or web-based applications.
Approximation of the exponential integral (well function) using sampling methods
Baalousha, Husam Musa
2015-04-01
Exponential integral (also known as well function) is often used in hydrogeology to solve Theis and Hantush equations. Many methods have been developed to approximate the exponential integral. Most of these methods are based on numerical approximations and are valid for a certain range of the argument value. This paper presents a new approach to approximate the exponential integral. The new approach is based on sampling methods. Three different sampling methods; Latin Hypercube Sampling (LHS), Orthogonal Array (OA), and Orthogonal Array-based Latin Hypercube (OA-LH) have been used to approximate the function. Different argument values, covering a wide range, have been used. The results of sampling methods were compared with results obtained by Mathematica software, which was used as a benchmark. All three sampling methods converge to the result obtained by Mathematica, at different rates. It was found that the orthogonal array (OA) method has the fastest convergence rate compared with LHS and OA-LH. The root mean square error RMSE of OA was in the order of 1E-08. This method can be used with any argument value, and can be used to solve other integrals in hydrogeology such as the leaky aquifer integral.
Discontinuous approximate molecular electronic wave-functions
International Nuclear Information System (INIS)
Stuebing, E.W.; Weare, J.H.; Parr, R.G.
1977-01-01
Following Kohn, Schlosser and Marcus and Weare and Parr an energy functional is defined for a molecular problem which is stationary in the neighborhood of the exact solution and permits the use of trial functions that are discontinuous. The functional differs from the functional of the standard Rayleigh--Ritz method in the replacement of the usual kinetic energy operators circumflex T(μ) with operators circumflex T'(μ) = circumflex T(μ) + circumflex I(μ) generates contributions from surfaces of nonsmooth behavior. If one uses the nabla PSI . nabla PSI way of writing the usual kinetic energy contributions, one must add surface integrals of the product of the average of nabla PSI and the change of PSI across surfaces of discontinuity. Various calculations are carried out for the hydrogen molecule-ion and the hydrogen molecule. It is shown that ab initio calculations on molecules can be carried out quite generally with a basis of atomic orbitals exactly obeying the zero-differential overlap (ZDO) condition, and a firm basis is thereby provided for theories of molecular electronic structure invoking the ZDO aoproximation. It is demonstrated that a valence bond theory employing orbitals exactly obeying ZDO can provide an adequate account of chemical bonding, and several suggestions are made regarding molecular orbital methods
An inductive algorithm for smooth approximation of functions
International Nuclear Information System (INIS)
Kupenova, T.N.
2011-01-01
An inductive algorithm is presented for smooth approximation of functions, based on the Tikhonov regularization method and applied to a specific kind of the Tikhonov parametric functional. The discrepancy principle is used for estimation of the regularization parameter. The principle of heuristic self-organization is applied for assessment of some parameters of the approximating function
Comparison of four support-vector based function approximators
de Kruif, B.J.; de Vries, Theodorus J.A.
2004-01-01
One of the uses of the support vector machine (SVM), as introduced in V.N. Vapnik (2000), is as a function approximator. The SVM and approximators based on it, approximate a relation in data by applying interpolation between so-called support vectors, being a limited number of samples that have been
Longitudinal functional principal component modelling via Stochastic Approximation Monte Carlo
Martinez, Josue G.
2010-06-01
The authors consider the analysis of hierarchical longitudinal functional data based upon a functional principal components approach. In contrast to standard frequentist approaches to selecting the number of principal components, the authors do model averaging using a Bayesian formulation. A relatively straightforward reversible jump Markov Chain Monte Carlo formulation has poor mixing properties and in simulated data often becomes trapped at the wrong number of principal components. In order to overcome this, the authors show how to apply Stochastic Approximation Monte Carlo (SAMC) to this problem, a method that has the potential to explore the entire space and does not become trapped in local extrema. The combination of reversible jump methods and SAMC in hierarchical longitudinal functional data is simplified by a polar coordinate representation of the principal components. The approach is easy to implement and does well in simulated data in determining the distribution of the number of principal components, and in terms of its frequentist estimation properties. Empirical applications are also presented.
Dynamic programming approach to optimization of approximate decision rules
Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata
2013-01-01
This paper is devoted to the study of an extension of dynamic programming approach which allows sequential optimization of approximate decision rules relative to the length and coverage. We introduce an uncertainty measure R(T) which is the number
Approximate Treatment of the Dirac Equation with Hyperbolic Potential Function
Durmus, Aysen
2018-03-01
The time independent Dirac equation is solved analytically for equal scalar and vector hyperbolic potential function in the presence of Greene and Aldrich approximation scheme. The bound state energy equation and spinor wave functions expressed by the hypergeometric function have been obtained in detail with asymptotic iteration approach. In order to indicate the accuracy of this different approach proposed to solve second order linear differential equations, we present that in the non-relativistic limit, analytical solutions of the Dirac equation converge to those of the Schrödinger one. We introduce numerical results of the theoretical analysis for hyperbolic potential function. Bound states corresponding to arbitrary values of n and l are reported for potential parameters covering a wide range of interaction. Also, we investigate relativistic vibrational energy spectra of alkali metal diatomic molecules in the different electronic states. It is observed that theoretical vibrational energy values are consistent with experimental Rydberg-Klein-Rees (RKR) results and vibrational energies of NaK, K_2 and KRb diatomic molecules interacting with hyperbolic potential smoothly converge to the experimental dissociation limit D_e=2508cm^{-1}, 254cm^{-1} and 4221cm^{-1}, respectively.
Quasi-fractional approximation to the Bessel functions
International Nuclear Information System (INIS)
Guerrero, P.M.L.
1989-01-01
In this paper the authors presents a simple Quasi-Fractional Approximation for Bessel Functions J ν (x), (- 1 ≤ ν < 0.5). This has been obtained by extending a method published which uses simultaneously power series and asymptotic expansions. Both functions, exact and approximated, coincide in at least two digits for positive x, and ν between - 1 and 0,4
Approximating Exponential and Logarithmic Functions Using Polynomial Interpolation
Gordon, Sheldon P.; Yang, Yajun
2017-01-01
This article takes a closer look at the problem of approximating the exponential and logarithmic functions using polynomials. Either as an alternative to or a precursor to Taylor polynomial approximations at the precalculus level, interpolating polynomials are considered. A measure of error is given and the behaviour of the error function is…
On root mean square approximation by exponential functions
Sharipov, Ruslan
2014-01-01
The problem of root mean square approximation of a square integrable function by finite linear combinations of exponential functions is considered. It is subdivided into linear and nonlinear parts. The linear approximation problem is solved. Then the nonlinear problem is studied in some particular example.
Bisetti, Fabrizio
2012-01-01
with the computational cost associated with the time integration of stiff, large chemical systems, a novel approach is proposed. The approach combines an exponential integrator and Krylov subspace approximations to the exponential function of the Jacobian matrix
Function approximation using combined unsupervised and supervised learning.
Andras, Peter
2014-03-01
Function approximation is one of the core tasks that are solved using neural networks in the context of many engineering problems. However, good approximation results need good sampling of the data space, which usually requires exponentially increasing volume of data as the dimensionality of the data increases. At the same time, often the high-dimensional data is arranged around a much lower dimensional manifold. Here we propose the breaking of the function approximation task for high-dimensional data into two steps: (1) the mapping of the high-dimensional data onto a lower dimensional space corresponding to the manifold on which the data resides and (2) the approximation of the function using the mapped lower dimensional data. We use over-complete self-organizing maps (SOMs) for the mapping through unsupervised learning, and single hidden layer neural networks for the function approximation through supervised learning. We also extend the two-step procedure by considering support vector machines and Bayesian SOMs for the determination of the best parameters for the nonlinear neurons in the hidden layer of the neural networks used for the function approximation. We compare the approximation performance of the proposed neural networks using a set of functions and show that indeed the neural networks using combined unsupervised and supervised learning outperform in most cases the neural networks that learn the function approximation using the original high-dimensional data.
Śmiga, Szymon; Fabiano, Eduardo; Laricchia, Savio; Constantin, Lucian A; Della Sala, Fabio
2015-04-21
We analyze the methodology and the performance of subsystem density functional theory (DFT) with meta-generalized gradient approximation (meta-GGA) exchange-correlation functionals for non-bonded molecular systems. Meta-GGA functionals depend on the Kohn-Sham kinetic energy density (KED), which is not known as an explicit functional of the density. Therefore, they cannot be directly applied in subsystem DFT calculations. We propose a Laplacian-level approximation to the KED which overcomes this limitation and provides a simple and accurate way to apply meta-GGA exchange-correlation functionals in subsystem DFT calculations. The so obtained density and energy errors, with respect to the corresponding supermolecular calculations, are comparable with conventional approaches, depending almost exclusively on the approximations in the non-additive kinetic embedding term. An embedding energy error decomposition explains the accuracy of our method.
Legendre-tau approximations for functional differential equations
Ito, K.; Teglas, R.
1986-01-01
The numerical approximation of solutions to linear retarded functional differential equations are considered using the so-called Legendre-tau method. The functional differential equation is first reformulated as a partial differential equation with a nonlocal boundary condition involving time-differentiation. The approximate solution is then represented as a truncated Legendre series with time-varying coefficients which satisfy a certain system of ordinary differential equations. The method is very easy to code and yields very accurate approximations. Convergence is established, various numerical examples are presented, and comparison between the latter and cubic spline approximation is made.
Precise analytic approximations for the Bessel function J1 (x)
Maass, Fernando; Martin, Pablo
2018-03-01
Precise and straightforward analytic approximations for the Bessel function J1 (x) have been found. Power series and asymptotic expansions have been used to determine the parameters of the approximation, which is as a bridge between both expansions, and it is a combination of rational and trigonometric functions multiplied with fractional powers of x. Here, several improvements with respect to the so called Multipoint Quasirational Approximation technique have been performed. Two procedures have been used to determine the parameters of the approximations. The maximum absolute errors are in both cases smaller than 0.01. The zeros of the approximation are also very precise with less than 0.04 per cent for the first one. A second approximation has been also determined using two more parameters, and in this way the accuracy has been increased to less than 0.001.
Distributed Approximating Functional Approach to Burgers' Equation ...
African Journals Online (AJOL)
This equation is similar to, but simpler than, the Navier-Stokes equation in fluid dynamics. To verify this advantage through some comparison studies, an exact series solution are also obtained. In addition, the presented scheme has numerically stable behavior. After demonstrating the convergence and accuracy of the ...
Efficient approximation of black-box functions and Pareto sets
Rennen, G.
2009-01-01
In the case of time-consuming simulation models or other so-called black-box functions, we determine a metamodel which approximates the relation between the input- and output-variables of the simulation model. To solve multi-objective optimization problems, we approximate the Pareto set, i.e. the
Reducing Approximation Error in the Fourier Flexible Functional Form
Directory of Open Access Journals (Sweden)
Tristan D. Skolrud
2017-12-01
Full Text Available The Fourier Flexible form provides a global approximation to an unknown data generating process. In terms of limiting function specification error, this form is preferable to functional forms based on second-order Taylor series expansions. The Fourier Flexible form is a truncated Fourier series expansion appended to a second-order expansion in logarithms. By replacing the logarithmic expansion with a Box-Cox transformation, we show that the Fourier Flexible form can reduce approximation error by 25% on average in the tails of the data distribution. The new functional form allows for nested testing of a larger set of commonly implemented functional forms.
Sinc-Approximations of Fractional Operators: A Computing Approach
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Gerd Baumann
2015-06-01
Full Text Available We discuss a new approach to represent fractional operators by Sinc approximation using convolution integrals. A spin off of the convolution representation is an effective inverse Laplace transform. Several examples demonstrate the application of the method to different practical problems.
Approximate Approaches to the One-Dimensional Finite Potential Well
Singh, Shilpi; Pathak, Praveen; Singh, Vijay A.
2011-01-01
The one-dimensional finite well is a textbook problem. We propose approximate approaches to obtain the energy levels of the well. The finite well is also encountered in semiconductor heterostructures where the carrier mass inside the well (m[subscript i]) is taken to be distinct from mass outside (m[subscript o]). A relevant parameter is the mass…
A Statistical Mechanics Approach to Approximate Analytical Bootstrap Averages
DEFF Research Database (Denmark)
Malzahn, Dorthe; Opper, Manfred
2003-01-01
We apply the replica method of Statistical Physics combined with a variational method to the approximate analytical computation of bootstrap averages for estimating the generalization error. We demonstrate our approach on regression with Gaussian processes and compare our results with averages...
On approximation and energy estimates for delta 6-convex functions.
Saleem, Muhammad Shoaib; Pečarić, Josip; Rehman, Nasir; Khan, Muhammad Wahab; Zahoor, Muhammad Sajid
2018-01-01
The smooth approximation and weighted energy estimates for delta 6-convex functions are derived in this research. Moreover, we conclude that if 6-convex functions are closed in uniform norm, then their third derivatives are closed in weighted [Formula: see text]-norm.
On approximation and energy estimates for delta 6-convex functions
Directory of Open Access Journals (Sweden)
Muhammad Shoaib Saleem
2018-02-01
Full Text Available Abstract The smooth approximation and weighted energy estimates for delta 6-convex functions are derived in this research. Moreover, we conclude that if 6-convex functions are closed in uniform norm, then their third derivatives are closed in weighted L2 $L^{2}$-norm.
Cheap contouring of costly functions: the Pilot Approximation Trajectory algorithm
International Nuclear Information System (INIS)
Huttunen, Janne M J; Stark, Philip B
2012-01-01
The Pilot Approximation Trajectory (PAT) contour algorithm can find the contour of a function accurately when it is not practical to evaluate the function on a grid dense enough to use a standard contour algorithm, for instance, when evaluating the function involves conducting a physical experiment or a computationally intensive simulation. PAT relies on an inexpensive pilot approximation to the function, such as interpolating from a sparse grid of inexact values, or solving a partial differential equation (PDE) numerically using a coarse discretization. For each level of interest, the location and ‘trajectory’ of an approximate contour of this pilot function are used to decide where to evaluate the original function to find points on its contour. Those points are joined by line segments to form the PAT approximation of the contour of the original function. Approximating a contour numerically amounts to estimating a lower level set of the function, the set of points on which the function does not exceed the contour level. The area of the symmetric difference between the true lower level set and the estimated lower level set measures the accuracy of the contour. PAT measures its own accuracy by finding an upper confidence bound for this area. In examples, PAT can estimate a contour more accurately than standard algorithms, using far fewer function evaluations than standard algorithms require. We illustrate PAT by constructing a confidence set for viscosity and thermal conductivity of a flowing gas from simulated noisy temperature measurements, a problem in which each evaluation of the function to be contoured requires solving a different set of coupled nonlinear PDEs. (paper)
Monoenergetic approximation of a polyenergetic beam: a theoretical approach
International Nuclear Information System (INIS)
Robinson, D.M.; Scrimger, J.W.
1991-01-01
There exist numerous occasions in which it is desirable to approximate the polyenergetic beams employed in radiation therapy by a beam of photons of a single energy. In some instances, commonly used rules of thumb for the selection of an appropriate energy may be valid. A more accurate approximate energy, however, may be determined by an analysis which takes into account both the spectral qualities of the beam and the material through which it passes. The theoretical basis of this method of analysis is presented in this paper. Experimental agreement with theory for a range of materials and beam qualities is also presented and demonstrates the validity of the theoretical approach taken. (author)
Complexity of Gaussian-Radial-Basis Networks Approximating Smooth Functions
Czech Academy of Sciences Publication Activity Database
Kainen, P.C.; Kůrková, Věra; Sanguineti, M.
2009-01-01
Roč. 25, č. 1 (2009), s. 63-74 ISSN 0885-064X R&D Projects: GA ČR GA201/08/1744 Institutional research plan: CEZ:AV0Z10300504 Keywords : Gaussian-radial-basis-function networks * rates of approximation * model complexity * variation norms * Bessel and Sobolev norms * tractability of approximation Subject RIV: IN - Informatics, Computer Science Impact factor: 1.227, year: 2009
Mathieu functions and its useful approximation for elliptical waveguides
Pillay, Shamini; Kumar, Deepak
2017-11-01
The standard form of the Mathieu differential equation is where a and q are real parameters and q > 0. In this paper we obtain closed formula for the generic term of expansions of modified Mathieu functions in terms of Bessel and modified Bessel functions in the following cases: Let ξ0 = ξ0, where i can take the values 1 and 2 corresponding to the first and the second boundary. These approximations also provide alternative methods for numerical evaluation of Mathieu functions.
Using function approximation to determine neural network accuracy
International Nuclear Information System (INIS)
Wichman, R.F.; Alexander, J.
2013-01-01
Many, if not most, control processes demonstrate nonlinear behavior in some portion of their operating range and the ability of neural networks to model non-linear dynamics makes them very appealing for control. Control of high reliability safety systems, and autonomous control in process or robotic applications, however, require accurate and consistent control and neural networks are only approximators of various functions so their degree of approximation becomes important. In this paper, the factors affecting the ability of a feed-forward back-propagation neural network to accurately approximate a non-linear function are explored. Compared to pattern recognition using a neural network for function approximation provides an easy and accurate method for determining the network's accuracy. In contrast to other techniques, we show that errors arising in function approximation or curve fitting are caused by the neural network itself rather than scatter in the data. A method is proposed that provides improvements in the accuracy achieved during training and resulting ability of the network to generalize after training. Binary input vectors provided a more accurate model than with scalar inputs and retraining using a small number of the outlier x,y pairs improved generalization. (author)
Analytical approximations to seawater optical phase functions of scattering
Haltrin, Vladimir I.
2004-11-01
This paper proposes a number of analytical approximations to the classic and recently measured seawater light scattering phase functions. The three types of analytical phase functions are derived: individual representations for 15 Petzold, 41 Mankovsky, and 91 Gulf of Mexico phase functions; collective fits to Petzold phase functions; and analytical representations that take into account dependencies between inherent optical properties of seawater. The proposed phase functions may be used for problems of radiative transfer, remote sensing, visibility and image propagation in natural waters of various turbidity.
Approximate approaches to the one-dimensional finite potential well
International Nuclear Information System (INIS)
Singh, Shilpi; Pathak, Praveen; Singh, Vijay A
2011-01-01
The one-dimensional finite well is a textbook problem. We propose approximate approaches to obtain the energy levels of the well. The finite well is also encountered in semiconductor heterostructures where the carrier mass inside the well (m i ) is taken to be distinct from mass outside (m o ). A relevant parameter is the mass discontinuity ratio β = m i /m o . To correctly account for the mass discontinuity, we apply the BenDaniel-Duke boundary condition. We obtain approximate solutions for two cases: when the well is shallow and when the well is deep. We compare the approximate results with the exact results and find that higher-order approximations are quite robust. For the shallow case, the approximate solution can be expressed in terms of a dimensionless parameter σ l = 2m o V 0 L 2 /ℎ 2 (or σ = β 2 σ l for the deep case). We show that the lowest-order results are related by a duality transform. We also discuss how the energy upscales with L (E∼1/L γ ) and obtain the exponent γ. Exponent γ → 2 when the well is sufficiently deep and β → 1. The ratio of the masses dictates the physics. Our presentation is pedagogical and should be useful to students on a first course on elementary quantum mechanics or low-dimensional semiconductors.
On Approximate Solutions of Functional Equations in Vector Lattices
Directory of Open Access Journals (Sweden)
Bogdan Batko
2014-01-01
Full Text Available We provide a method of approximation of approximate solutions of functional equations in the class of functions acting into a Riesz space (algebra. The main aim of the paper is to provide a general theorem that can act as a tool applicable to a possibly wide class of functional equations. The idea is based on the use of the Spectral Representation Theory for Riesz spaces. The main result will be applied to prove the stability of an alternative Cauchy functional equation F(x+y+F(x+F(y≠0⇒F(x+y=F(x+F(y in Riesz spaces, the Cauchy equation with squares F(x+y2=(F(x+F(y2 in f-algebras, and the quadratic functional equation F(x+y+F(x-y=2F(x+2F(y in Riesz spaces.
Approximation of the Doppler broadening function by Frobenius method
International Nuclear Information System (INIS)
Palma, Daniel A.P.; Martinez, Aquilino S.; Silva, Fernando C.
2005-01-01
An analytical approximation of the Doppler broadening function ψ(x,ξ) is proposed. This approximation is based on the solution of the differential equation for ψ(x,ξ) using the methods of Frobenius and the parameters variation. The analytical form derived for ψ(x,ξ) in terms of elementary functions is very simple and precise. It can be useful for applications related to the treatment of nuclear resonances mainly for the calculations of multigroup parameters and self-protection factors of the resonances, being the last used to correct microscopic cross-sections measurements by the activation technique. (author)
Approximate convex hull of affine iterated function system attractors
International Nuclear Information System (INIS)
Mishkinis, Anton; Gentil, Christian; Lanquetin, Sandrine; Sokolov, Dmitry
2012-01-01
Highlights: ► We present an iterative algorithm to approximate affine IFS attractor convex hull. ► Elimination of the interior points significantly reduces the complexity. ► To optimize calculations, we merge the convex hull images at each iteration. ► Approximation by ellipses increases speed of convergence to the exact convex hull. ► We present a method of the output convex hull simplification. - Abstract: In this paper, we present an algorithm to construct an approximate convex hull of the attractors of an affine iterated function system (IFS). We construct a sequence of convex hull approximations for any required precision using the self-similarity property of the attractor in order to optimize calculations. Due to the affine properties of IFS transformations, the number of points considered in the construction is reduced. The time complexity of our algorithm is a linear function of the number of iterations and the number of points in the output approximate convex hull. The number of iterations and the execution time increases logarithmically with increasing accuracy. In addition, we introduce a method to simplify the approximate convex hull without loss of accuracy.
Singlet structure function F_1 in double-logarithmic approximation
Ermolaev, B. I.; Troyan, S. I.
2018-03-01
The conventional ways to calculate the perturbative component of the DIS singlet structure function F_1 involve approaches based on BFKL which account for the single-logarithmic contributions accompanying the Born factor 1 / x. In contrast, we account for the double-logarithmic (DL) contributions unrelated to 1 / x and because of that they were disregarded as negligibly small. We calculate the singlet F_1 in the double-logarithmic approximation (DLA) and account at the same time for the running α _s effects. We start with a total resummation of both quark and gluon DL contributions and obtain the explicit expression for F_1 in DLA. Then, applying the saddle-point method, we calculate the small- x asymptotics of F_1, which proves to be of the Regge form with the leading singularity ω _0 = 1.066. Its large value compensates for the lack of the factor 1 / x in the DLA contributions. Therefore, this Reggeon can be identified as a new Pomeron, which can be quite important for the description of all QCD processes involving the vacuum (Pomeron) exchanges at very high energies. We prove that the expression for the small- x asymptotics of F_1 scales: it depends on a single variable Q^2/x^2 only instead of x and Q^2 separately. Finally, we show that the small- x asymptotics reliably represent F_1 at x ≤ 10^{-6}.
Integral approximants for functions of higher monodromic dimension
Energy Technology Data Exchange (ETDEWEB)
Baker, G.A. Jr.
1987-01-01
In addition to the description of multiform, locally analytic functions as covering a many sheeted version of the complex plane, Riemann also introduced the notion of considering them as describing a space whose ''monodromic'' dimension is the number of linearly independent coverings by the monogenic analytic function at each point of the complex plane. I suggest that this latter concept is natural for integral approximants (sub-class of Hermite-Pade approximants) and discuss results for both ''horizontal'' and ''diagonal'' sequences of approximants. Some theorems are now available in both cases and make clear the natural domain of convergence of the horizontal sequences is a disk centered on the origin and that of the diagonal sequences is a suitably cut complex-plane together with its identically cut pendant Riemann sheets. Some numerical examples have also been computed.
Sequential function approximation on arbitrarily distributed point sets
Wu, Kailiang; Xiu, Dongbin
2018-02-01
We present a randomized iterative method for approximating unknown function sequentially on arbitrary point set. The method is based on a recently developed sequential approximation (SA) method, which approximates a target function using one data point at each step and avoids matrix operations. The focus of this paper is on data sets with highly irregular distribution of the points. We present a nearest neighbor replacement (NNR) algorithm, which allows one to sample the irregular data sets in a near optimal manner. We provide mathematical justification and error estimates for the NNR algorithm. Extensive numerical examples are also presented to demonstrate that the NNR algorithm can deliver satisfactory convergence for the SA method on data sets with high irregularity in their point distributions.
Pade approximants for entire functions with regularly decreasing Taylor coefficients
International Nuclear Information System (INIS)
Rusak, V N; Starovoitov, A P
2002-01-01
For a class of entire functions the asymptotic behaviour of the Hadamard determinants D n,m as 0≤m≤m(n)→∞ and n→∞ is described. This enables one to study the behaviour of parabolic sequences from Pade and Chebyshev tables for many individual entire functions. The central result of the paper is as follows: for some sequences {(n,m(n))} in certain classes of entire functions (with regular Taylor coefficients) the Pade approximants {π n,m(n) }, which provide the locally best possible rational approximations, converge to the given function uniformly on the compact set D={z:|z|≤1} with asymptotically best rate
Approximation solutions for indifference pricing under general utility functions
Chen, An; Pelsser, Antoon; Vellekoop, M.H.
2008-01-01
With the aid of Taylor-based approximations, this paper presents results for pricing insurance contracts by using indifference pricing under general utility functions. We discuss the connection between the resulting "theoretical" indifference prices and the pricing rule-of-thumb that practitioners
Animating Nested Taylor Polynomials to Approximate a Function
Mazzone, Eric F.; Piper, Bruce R.
2010-01-01
The way that Taylor polynomials approximate functions can be demonstrated by moving the center point while keeping the degree fixed. These animations are particularly nice when the Taylor polynomials do not intersect and form a nested family. We prove a result that shows when this nesting occurs. The animations can be shown in class or…
Approximate Solutions for Indifference Pricing under General Utility Functions
Chen, A.; Pelsser, A.; Vellekoop, M.
2007-01-01
With the aid of Taylor-based approximations, this paper presents results for pricing insurance contracts by using indifference pricing under general utility functions. We discuss the connection between the resulting "theoretical" indifference prices and the pricing rule-of-thumb that practitioners
Applications exponential approximation by integer shifts of Gaussian functions
Directory of Open Access Journals (Sweden)
S. M. Sitnik
2013-01-01
Full Text Available In this paper we consider approximations of functions using integer shifts of Gaussians – quadratic exponentials. A method is proposed to find coefficients of node functions by solving linear systems of equations. The explicit formula for the determinant of the system is found, based on it solvability of linear system under consideration is proved and uniqueness of its solution. We compare results with known ones and briefly indicate applications to signal theory.
An approximate approach to quantum mechanical study of biomacromolecules
Chen, Xihua
method/basis-set levels of the quantum chemical calculation on the MFCC-downhill simplex optimization are also discussed. Finally, the MFCC-downhill simplex method is tested, as a general multiatomic case study, on a molecular system of cyclo-AAGAGG·H 2O to optimize the binding structure of water molecule to the fixed cyclohexapeptide. The MFCC-downhill simplex optimization results in good agreement with the crystal structure. The MFCC-downhill simplex method should be applicable to optimize the structures of ligands that bind to biomacromolecules such as proteins and DNAs. In Chapter 4, we propose a new approximate method for efficient calculation of biomacromolecular electronic properties, using a Density Matrix (DM) scheme which is integrated with the MFCC approach. In this MFCC-DM method, a biomacro-molecule such as a protein is partitioned by an MFCC scheme into properly capped fragments and concaps whose density matrices are calculated by conventional ab initio methods. These sub-system density matrices are then assembled to construct the full system density matrix which is finally employed to calculate the electronic energy, dipole moment, electronic density, electrostatic potential, etc., of the protein using Hartree-Fock or Density Functional Theory methods. By this MFCC-DM method, the self-consistent field (SCF) procedure for solving the full Hamiltonian problem is circumvented. Two implementations of this approach, MFCC-SDM and MFCC-GDM, are discussed. Systematic numerical studies are carried out on a series of extended polyglycines CH3CO-(GLY) n-NHCH3 (n=3-25) and excellent results are obtained. In Chapter 5, we present an improvement of MFCC-DM method and introduce a pairwise interaction correction (PIC) with which the MFCC-DM method is applicable to study a real-world protein with short-range structural complexity such as hydrogen bonding and close contact. In this MFCC-DM-PIC method, a protein molecule is partitioned into properly capped fragments and
Bessel collocation approach for approximate solutions of Hantavirus infection model
Directory of Open Access Journals (Sweden)
Suayip Yuzbasi
2017-11-01
Full Text Available In this study, a collocation method is introduced to find the approximate solutions of Hantavirus infection model which is a system of nonlinear ordinary differential equations. The method is based on the Bessel functions of the first kind, matrix operations and collocation points. This method converts Hantavirus infection model into a matrix equation in terms of the Bessel functions of first kind, matrix operations and collocation points. The matrix equation corresponds to a system of nonlinear equations with the unknown Bessel coefficients. The reliability and efficiency of the suggested scheme are demonstrated by numerical applications and all numerical calculations have been done by using a program written in Maple.
Are there approximate relations among transverse momentum dependent distribution functions?
Energy Technology Data Exchange (ETDEWEB)
Harutyun AVAKIAN; Anatoli Efremov; Klaus Goeke; Andreas Metz; Peter Schweitzer; Tobias Teckentrup
2007-10-11
Certain {\\sl exact} relations among transverse momentum dependent parton distribution functions due to QCD equations of motion turn into {\\sl approximate} ones upon the neglect of pure twist-3 terms. On the basis of available data from HERMES we test the practical usefulness of one such ``Wandzura-Wilczek-type approximation'', namely of that connecting $h_{1L}^{\\perp(1)a}(x)$ to $h_L^a(x)$, and discuss how it can be further tested by future CLAS and COMPASS data.
Strong semiclassical approximation of Wigner functions for the Hartree dynamics
Athanassoulis, Agissilaos; Paul, Thierry; Pezzotti, Federica; Pulvirenti, Mario
2011-01-01
We consider the Wigner equation corresponding to a nonlinear Schrödinger evolution of the Hartree type in the semiclassical limit h → 0. Under appropriate assumptions on the initial data and the interaction potential, we show that the Wigner function is close in L 2 to its weak limit, the solution of the corresponding Vlasov equation. The strong approximation allows the construction of semiclassical operator-valued observables, approximating their quantum counterparts in Hilbert-Schmidt topology. The proof makes use of a pointwise-positivity manipulation, which seems necessary in working with the L 2 norm and the precise form of the nonlinearity. We employ the Husimi function as a pivot between the classical probability density and the Wigner function, which - as it is well known - is not pointwise positive in general.
Quantal density functional theory II. Approximation methods and applications
International Nuclear Information System (INIS)
Sahni, Viraht
2010-01-01
This book is on approximation methods and applications of Quantal Density Functional Theory (QDFT), a new local effective-potential-energy theory of electronic structure. What distinguishes the theory from traditional density functional theory is that the electron correlations due to the Pauli exclusion principle, Coulomb repulsion, and the correlation contribution to the kinetic energy -- the Correlation-Kinetic effects -- are separately and explicitly defined. As such it is possible to study each property of interest as a function of the different electron correlations. Approximations methods based on the incorporation of different electron correlations, as well as a many-body perturbation theory within the context of QDFT, are developed. The applications are to the few-electron inhomogeneous electron gas systems in atoms and molecules, as well as to the many-electron inhomogeneity at metallic surfaces. (orig.)
Approximation methods for the partition functions of anharmonic systems
International Nuclear Information System (INIS)
Lew, P.; Ishida, T.
1979-07-01
The analytical approximations for the classical, quantum mechanical and reduced partition functions of the diatomic molecule oscillating internally under the influence of the Morse potential have been derived and their convergences have been tested numerically. This successful analytical method is used in the treatment of anharmonic systems. Using Schwinger perturbation method in the framework of second quantization formulism, the reduced partition function of polyatomic systems can be put into an expression which consists separately of contributions from the harmonic terms, Morse potential correction terms and interaction terms due to the off-diagonal potential coefficients. The calculated results of the reduced partition function from the approximation method on the 2-D and 3-D model systems agree well with the numerical exact calculations
On the approximation of the limit cycles function
Directory of Open Access Journals (Sweden)
L. Cherkas
2007-11-01
Full Text Available We consider planar vector fields depending on a real parameter. It is assumed that this vector field has a family of limit cycles which can be described by means of the limit cycles function $l$. We prove a relationship between the multiplicity of a limit cycle of this family and the order of a zero of the limit cycles function. Moreover, we present a procedure to approximate $l(x$, which is based on the Newton scheme applied to the Poincaré function and represents a continuation method. Finally, we demonstrate the effectiveness of the proposed procedure by means of a Liénard system.
Numerical approximations of difference functional equations and applications
Directory of Open Access Journals (Sweden)
Zdzisław Kamont
2005-01-01
Full Text Available We give a theorem on the error estimate of approximate solutions for difference functional equations of the Volterra type. We apply this general result in the investigation of the stability of difference schemes generated by nonlinear first order partial differential functional equations and by parabolic problems. We show that all known results on difference methods for initial or initial boundary value problems can be obtained as particular cases of this general and simple result. We assume that the right hand sides of equations satisfy nonlinear estimates of the Perron type with respect to functional variables.
Approximate models for the analysis of laser velocimetry correlation functions
International Nuclear Information System (INIS)
Robinson, D.P.
1981-01-01
Velocity distributions in the subchannels of an eleven pin test section representing a slice through a Fast Reactor sub-assembly were measured with a dual beam laser velocimeter system using a Malvern K 7023 digital photon correlator for signal processing. Two techniques were used for data reduction of the correlation function to obtain velocity and turbulence values. Whilst both techniques were in excellent agreement on the velocity, marked discrepancies were apparent in the turbulence levels. As a consequence of this the turbulence data were not reported. Subsequent investigation has shown that the approximate technique used as the basis of Malvern's Data Processor 7023V is restricted in its range of application. In this note alternative approximate models are described and evaluated. The objective of this investigation was to develop an approximate model which could be used for on-line determination of the turbulence level. (author)
Corrected Fourier series and its application to function approximation
Directory of Open Access Journals (Sweden)
Qing-Hua Zhang
2005-01-01
Full Text Available Any quasismooth function f(x in a finite interval [0,x0], which has only a finite number of finite discontinuities and has only a finite number of extremes, can be approximated by a uniformly convergent Fourier series and a correction function. The correction function consists of algebraic polynomials and Heaviside step functions and is required by the aperiodicity at the endpoints (i.e., f(0≠f(x0 and the finite discontinuities in between. The uniformly convergent Fourier series and the correction function are collectively referred to as the corrected Fourier series. We prove that in order for the mth derivative of the Fourier series to be uniformly convergent, the order of the polynomial need not exceed (m+1. In other words, including the no-more-than-(m+1 polynomial has eliminated the Gibbs phenomenon of the Fourier series until its mth derivative. The corrected Fourier series is then applied to function approximation; the procedures to determine the coefficients of the corrected Fourier series are illustrated in detail using examples.
Approximate inference for spatial functional data on massively parallel processors
DEFF Research Database (Denmark)
Raket, Lars Lau; Markussen, Bo
2014-01-01
With continually increasing data sizes, the relevance of the big n problem of classical likelihood approaches is greater than ever. The functional mixed-effects model is a well established class of models for analyzing functional data. Spatial functional data in a mixed-effects setting...... in linear time. An extremely efficient GPU implementation is presented, and the proposed methods are illustrated by conducting a classical statistical analysis of 2D chromatography data consisting of more than 140 million spatially correlated observation points....
Rational function approximation method for discrete ordinates problems in slab geometry
International Nuclear Information System (INIS)
Leal, Andre Luiz do C.; Barros, Ricardo C.
2009-01-01
In this work we use rational function approaches to obtain the transfer functions that appear in the spectral Green's function (SGF) auxiliary equations for one-speed isotropic scattering SN equations in one-dimensional Cartesian geometry. For this task we use the computation of the Pade approximants to compare the results with the standard SGF method's applied to deep penetration problems in homogeneous domains. This work is a preliminary investigation of a new proposal for handling leakage terms that appear in the two transverse integrated one-dimensional SN equations in the exponential SGF method (SGF-ExpN). Numerical results are presented to illustrate the rational function approximation accuracy. (author)
Approximated Function Based Spectral Gradient Algorithm for Sparse Signal Recovery
Directory of Open Access Journals (Sweden)
Weifeng Wang
2014-02-01
Full Text Available Numerical algorithms for the l0-norm regularized non-smooth non-convex minimization problems have recently became a topic of great interest within signal processing, compressive sensing, statistics, and machine learning. Nevertheless, the l0-norm makes the problem combinatorial and generally computationally intractable. In this paper, we construct a new surrogate function to approximate l0-norm regularization, and subsequently make the discrete optimization problem continuous and smooth. Then we use the well-known spectral gradient algorithm to solve the resulting smooth optimization problem. Experiments are provided which illustrate this method is very promising.
Big geo data surface approximation using radial basis functions: A comparative study
Majdisova, Zuzana; Skala, Vaclav
2017-12-01
Approximation of scattered data is often a task in many engineering problems. The Radial Basis Function (RBF) approximation is appropriate for big scattered datasets in n-dimensional space. It is a non-separable approximation, as it is based on the distance between two points. This method leads to the solution of an overdetermined linear system of equations. In this paper the RBF approximation methods are briefly described, a new approach to the RBF approximation of big datasets is presented, and a comparison for different Compactly Supported RBFs (CS-RBFs) is made with respect to the accuracy of the computation. The proposed approach uses symmetry of a matrix, partitioning the matrix into blocks and data structures for storage of the sparse matrix. The experiments are performed for synthetic and real datasets.
Dynamic programming approach to optimization of approximate decision rules
Amin, Talha
2013-02-01
This paper is devoted to the study of an extension of dynamic programming approach which allows sequential optimization of approximate decision rules relative to the length and coverage. We introduce an uncertainty measure R(T) which is the number of unordered pairs of rows with different decisions in the decision table T. For a nonnegative real number β, we consider β-decision rules that localize rows in subtables of T with uncertainty at most β. Our algorithm constructs a directed acyclic graph Δβ(T) which nodes are subtables of the decision table T given by systems of equations of the kind "attribute = value". This algorithm finishes the partitioning of a subtable when its uncertainty is at most β. The graph Δβ(T) allows us to describe the whole set of so-called irredundant β-decision rules. We can describe all irredundant β-decision rules with minimum length, and after that among these rules describe all rules with maximum coverage. We can also change the order of optimization. The consideration of irredundant rules only does not change the results of optimization. This paper contains also results of experiments with decision tables from UCI Machine Learning Repository. © 2012 Elsevier Inc. All rights reserved.
Aarts, Ronald M; Janssen, Augustus J E M
2016-12-01
The Struve functions H n (z), n=0, 1, ... are approximated in a simple, accurate form that is valid for all z≥0. The authors previously treated the case n = 1 that arises in impedance calculations for the rigid-piston circular radiator mounted in an infinite planar baffle [Aarts and Janssen, J. Acoust. Soc. Am. 113, 2635-2637 (2003)]. The more general Struve functions occur when other acoustical quantities and/or non-rigid pistons are considered. The key step in the paper just cited is to express H 1 (z) as (2/π)-J 0 (z)+(2/π) I(z), where J 0 is the Bessel function of order zero and the first kind and I(z) is the Fourier cosine transform of [(1-t)/(1+t)] 1/2 , 0≤t≤1. The square-root function is optimally approximated by a linear function ĉt+d̂, 0≤t≤1, and the resulting approximated Fourier integral is readily computed explicitly in terms of sin z/z and (1-cos z)/z 2 . The same approach has been used by Maurel, Pagneux, Barra, and Lund [Phys. Rev. B 75, 224112 (2007)] to approximate H 0 (z) for all z≥0. In the present paper, the square-root function is optimally approximated by a piecewise linear function consisting of two linear functions supported by [0,t̂ 0 ] and [t̂ 0 ,1] with t̂ 0 the optimal take-over point. It is shown that the optimal two-piece linear function is actually continuous at the take-over point, causing a reduction of the additional complexity in the resulting approximations of H 0 and H 1 . Furthermore, this allows analytic computation of the optimal two-piece linear function. By using the two-piece instead of the one-piece linear approximation, the root mean square approximation error is reduced by roughly a factor of 3 while the maximum approximation error is reduced by a factor of 4.5 for H 0 and of 2.6 for H 1 . Recursion relations satisfied by Struve functions, initialized with the approximations of H 0 and H 1 , yield approximations for higher order Struve functions.
Diffusive Wave Approximation to the Shallow Water Equations: Computational Approach
Collier, Nathan; Radwan, Hany; Dalcin, Lisandro; Calo, Victor M.
2011-01-01
We discuss the use of time adaptivity applied to the one dimensional diffusive wave approximation to the shallow water equations. A simple and computationally economical error estimator is discussed which enables time-step size adaptivity
DEFF Research Database (Denmark)
Øjelund, Henrik; Sadegh, Payman
2000-01-01
be obtained. This paper presents a new approach for system modelling under partial (global) information (or the so called Gray-box modelling) that seeks to perserve the benefits of the global as well as local methodologies sithin a unified framework. While the proposed technique relies on local approximations......Local function approximations concern fitting low order models to weighted data in neighbourhoods of the points where the approximations are desired. Despite their generality and convenience of use, local models typically suffer, among others, from difficulties arising in physical interpretation...... simultaneously with the (local estimates of) function values. The approach is applied to modelling of a linear time variant dynamic system under prior linear time invariant structure where local regression fails as a result of high dimensionality....
Directory of Open Access Journals (Sweden)
Irina-Carmen ANDREI
2017-09-01
Full Text Available Following the demands of the design and performance analysis in case of liquid fuel propelled rocket engines, as well as the trajectory optimization, the development of efficient codes, which frequently need to call the Fuel Combustion Charts, became an important matter. This paper presents an efficient solution to the issue; the author has developed an original approach to determine the non-linear approximation function of two variables: the chamber pressure and the nozzle exit pressure ratio. The numerical algorithm based on this two variable approximation function is more efficient due to its simplicity, capability to providing numerical accuracy and prospects for an increased convergence rate of the optimization codes.
A full scale approximation of covariance functions for large spatial data sets
Sang, Huiyan
2011-10-10
Gaussian process models have been widely used in spatial statistics but face tremendous computational challenges for very large data sets. The model fitting and spatial prediction of such models typically require O(n 3) operations for a data set of size n. Various approximations of the covariance functions have been introduced to reduce the computational cost. However, most existing approximations cannot simultaneously capture both the large- and the small-scale spatial dependence. A new approximation scheme is developed to provide a high quality approximation to the covariance function at both the large and the small spatial scales. The new approximation is the summation of two parts: a reduced rank covariance and a compactly supported covariance obtained by tapering the covariance of the residual of the reduced rank approximation. Whereas the former part mainly captures the large-scale spatial variation, the latter part captures the small-scale, local variation that is unexplained by the former part. By combining the reduced rank representation and sparse matrix techniques, our approach allows for efficient computation for maximum likelihood estimation, spatial prediction and Bayesian inference. We illustrate the new approach with simulated and real data sets. © 2011 Royal Statistical Society.
A full scale approximation of covariance functions for large spatial data sets
Sang, Huiyan; Huang, Jianhua Z.
2011-01-01
Gaussian process models have been widely used in spatial statistics but face tremendous computational challenges for very large data sets. The model fitting and spatial prediction of such models typically require O(n 3) operations for a data set of size n. Various approximations of the covariance functions have been introduced to reduce the computational cost. However, most existing approximations cannot simultaneously capture both the large- and the small-scale spatial dependence. A new approximation scheme is developed to provide a high quality approximation to the covariance function at both the large and the small spatial scales. The new approximation is the summation of two parts: a reduced rank covariance and a compactly supported covariance obtained by tapering the covariance of the residual of the reduced rank approximation. Whereas the former part mainly captures the large-scale spatial variation, the latter part captures the small-scale, local variation that is unexplained by the former part. By combining the reduced rank representation and sparse matrix techniques, our approach allows for efficient computation for maximum likelihood estimation, spatial prediction and Bayesian inference. We illustrate the new approach with simulated and real data sets. © 2011 Royal Statistical Society.
Controllability distributions and systems approximations: a geometric approach
Ruiz, A.C.; Nijmeijer, Henk
1994-01-01
Given a nonlinear system we determine a relation at an equilibrium between controllability distributions defined for a nonlinear system and a Taylor series approximation of it. The value of such a relation is appreciated if we recall that the solvability conditions as well as the solutions to some
Controllability distributions and systems approximations: a geometric approach
Ruiz, A.C.; Nijmeijer, Henk
1992-01-01
Given a nonlinear system, a relation between controllability distributions defined for a nonlinear system and a Taylor series approximation of it is determined. Special attention is given to this relation at the equilibrium. It is known from nonlinear control theory that the solvability conditions
H4: A challenging system for natural orbital functional approximations
International Nuclear Information System (INIS)
Ramos-Cordoba, Eloy; Lopez, Xabier; Piris, Mario; Matito, Eduard
2015-01-01
The correct description of nondynamic correlation by electronic structure methods not belonging to the multireference family is a challenging issue. The transition of D 2h to D 4h symmetry in H 4 molecule is among the most simple archetypal examples to illustrate the consequences of missing nondynamic correlation effects. The resurgence of interest in density matrix functional methods has brought several new methods including the family of Piris Natural Orbital Functionals (PNOF). In this work, we compare PNOF5 and PNOF6, which include nondynamic electron correlation effects to some extent, with other standard ab initio methods in the H 4 D 4h /D 2h potential energy surface (PES). Thus far, the wrongful behavior of single-reference methods at the D 2h –D 4h transition of H 4 has been attributed to wrong account of nondynamic correlation effects, whereas in geminal-based approaches, it has been assigned to a wrong coupling of spins and the localized nature of the orbitals. We will show that actually interpair nondynamic correlation is the key to a cusp-free qualitatively correct description of H 4 PES. By introducing interpair nondynamic correlation, PNOF6 is shown to avoid cusps and provide the correct smooth PES features at distances close to the equilibrium, total and local spin properties along with the correct electron delocalization, as reflected by natural orbitals and multicenter delocalization indices
H4: A challenging system for natural orbital functional approximations
Ramos-Cordoba, Eloy; Lopez, Xabier; Piris, Mario; Matito, Eduard
2015-10-01
The correct description of nondynamic correlation by electronic structure methods not belonging to the multireference family is a challenging issue. The transition of D2h to D4h symmetry in H4 molecule is among the most simple archetypal examples to illustrate the consequences of missing nondynamic correlation effects. The resurgence of interest in density matrix functional methods has brought several new methods including the family of Piris Natural Orbital Functionals (PNOF). In this work, we compare PNOF5 and PNOF6, which include nondynamic electron correlation effects to some extent, with other standard ab initio methods in the H4 D4h/D2h potential energy surface (PES). Thus far, the wrongful behavior of single-reference methods at the D2h-D4h transition of H4 has been attributed to wrong account of nondynamic correlation effects, whereas in geminal-based approaches, it has been assigned to a wrong coupling of spins and the localized nature of the orbitals. We will show that actually interpair nondynamic correlation is the key to a cusp-free qualitatively correct description of H4 PES. By introducing interpair nondynamic correlation, PNOF6 is shown to avoid cusps and provide the correct smooth PES features at distances close to the equilibrium, total and local spin properties along with the correct electron delocalization, as reflected by natural orbitals and multicenter delocalization indices.
An Approximation Approach for Solving the Subpath Planning Problem
Safilian, Masoud; Tashakkori, S. Mehdi; Eghbali, Sepehr; Safilian, Aliakbar
2016-01-01
The subpath planning problem is a branch of the path planning problem, which has widespread applications in automated manufacturing process as well as vehicle and robot navigation. This problem is to find the shortest path or tour subject for travelling a set of given subpaths. The current approaches for dealing with the subpath planning problem are all based on meta-heuristic approaches. It is well-known that meta-heuristic based approaches have several deficiencies. To address them, we prop...
Earth's core convection: Boussinesq approximation or incompressible approach?
Czech Academy of Sciences Publication Activity Database
Anufriev, A. P.; Hejda, Pavel
2010-01-01
Roč. 104, č. 1 (2010), s. 65-83 ISSN 0309-1929 R&D Projects: GA AV ČR IAA300120704 Grant - others:INTAS(XE) 03-51-5807 Institutional research plan: CEZ:AV0Z30120515 Keywords : geodynamic models * core convection * Boussinesq approximation Subject RIV: DE - Earth Magnetism, Geodesy, Geography Impact factor: 0.831, year: 2010
Mean-field approximation for spacing distribution functions in classical systems
González, Diego Luis; Pimpinelli, Alberto; Einstein, T. L.
2012-01-01
We propose a mean-field method to calculate approximately the spacing distribution functions p(n)(s) in one-dimensional classical many-particle systems. We compare our method with two other commonly used methods, the independent interval approximation and the extended Wigner surmise. In our mean-field approach, p(n)(s) is calculated from a set of Langevin equations, which are decoupled by using a mean-field approximation. We find that in spite of its simplicity, the mean-field approximation provides good results in several systems. We offer many examples illustrating that the three previously mentioned methods give a reasonable description of the statistical behavior of the system. The physical interpretation of each method is also discussed.
An approximate methods approach to probabilistic structural analysis
Mcclung, R. C.; Millwater, H. R.; Wu, Y.-T.; Thacker, B. H.; Burnside, O. H.
1989-01-01
A probabilistic structural analysis method (PSAM) is described which makes an approximate calculation of the structural response of a system, including the associated probabilistic distributions, with minimal computation time and cost, based on a simplified representation of the geometry, loads, and material. The method employs the fast probability integration (FPI) algorithm of Wu and Wirsching. Typical solution strategies are illustrated by formulations for a representative critical component chosen from the Space Shuttle Main Engine (SSME) as part of a major NASA-sponsored program on PSAM. Typical results are presented to demonstrate the role of the methodology in engineering design and analysis.
Diffusive Wave Approximation to the Shallow Water Equations: Computational Approach
Collier, Nathan
2011-05-14
We discuss the use of time adaptivity applied to the one dimensional diffusive wave approximation to the shallow water equations. A simple and computationally economical error estimator is discussed which enables time-step size adaptivity. This robust adaptive time discretization corrects the initial time step size to achieve a user specified bound on the discretization error and allows time step size variations of several orders of magnitude. In particular, in the one dimensional results presented in this work feature a change of four orders of magnitudes for the time step over the entire simulation.
Approximate dynamic programming approaches for appointment scheduling with patient preferences.
Li, Xin; Wang, Jin; Fung, Richard Y K
2018-04-01
During the appointment booking process in out-patient departments, the level of patient satisfaction can be affected by whether or not their preferences can be met, including the choice of physicians and preferred time slot. In addition, because the appointments are sequential, considering future possible requests is also necessary for a successful appointment system. This paper proposes a Markov decision process model for optimizing the scheduling of sequential appointments with patient preferences. In contrast to existing models, the evaluation of a booking decision in this model focuses on the extent to which preferences are satisfied. Characteristics of the model are analysed to develop a system for formulating booking policies. Based on these characteristics, two types of approximate dynamic programming algorithms are developed to avoid the curse of dimensionality. Experimental results suggest directions for further fine-tuning of the model, as well as improving the efficiency of the two proposed algorithms. Copyright © 2018 Elsevier B.V. All rights reserved.
CSIR Research Space (South Africa)
Kok, S
2012-07-01
Full Text Available continuously as the correlation function hyper-parameters approach zero. Since the global minimizer of the maximum likelihood function is an asymptote in this case, it is unclear if maximum likelihood estimation (MLE) remains valid. Numerical ill...
Wavelet series approximation using wavelet function with compactly ...
African Journals Online (AJOL)
The Wavelets generated by Scaling Function with Compactly Support are useful in various applications especially for reconstruction of functions. Generally, the computational process will be faster if Scaling Function support descends, so computational errors are summarized from one level to another level. In this article, the ...
Piecewise quadratic Lyapunov functions for stability verification of approximate explicit MPC
Directory of Open Access Journals (Sweden)
Morten Hovd
2010-04-01
Full Text Available Explicit MPC of constrained linear systems is known to result in a piecewise affine controller and therefore also piecewise affine closed loop dynamics. The complexity of such analytic formulations of the control law can grow exponentially with the prediction horizon. The suboptimal solutions offer a trade-off in terms of complexity and several approaches can be found in the literature for the construction of approximate MPC laws. In the present paper a piecewise quadratic (PWQ Lyapunov function is used for the stability verification of an of approximate explicit Model Predictive Control (MPC. A novel relaxation method is proposed for the LMI criteria on the Lyapunov function design. This relaxation is applicable to the design of PWQ Lyapunov functions for discrete-time piecewise affine systems in general.
Directory of Open Access Journals (Sweden)
Yunfeng Wu
2014-01-01
Full Text Available This paper presents a novel adaptive linear and normalized combination (ALNC method that can be used to combine the component radial basis function networks (RBFNs to implement better function approximation and regression tasks. The optimization of the fusion weights is obtained by solving a constrained quadratic programming problem. According to the instantaneous errors generated by the component RBFNs, the ALNC is able to perform the selective ensemble of multiple leaners by adaptively adjusting the fusion weights from one instance to another. The results of the experiments on eight synthetic function approximation and six benchmark regression data sets show that the ALNC method can effectively help the ensemble system achieve a higher accuracy (measured in terms of mean-squared error and the better fidelity (characterized by normalized correlation coefficient of approximation, in relation to the popular simple average, weighted average, and the Bagging methods.
Multi-level methods and approximating distribution functions
International Nuclear Information System (INIS)
Wilson, D.; Baker, R. E.
2016-01-01
Biochemical reaction networks are often modelled using discrete-state, continuous-time Markov chains. System statistics of these Markov chains usually cannot be calculated analytically and therefore estimates must be generated via simulation techniques. There is a well documented class of simulation techniques known as exact stochastic simulation algorithms, an example of which is Gillespie’s direct method. These algorithms often come with high computational costs, therefore approximate stochastic simulation algorithms such as the tau-leap method are used. However, in order to minimise the bias in the estimates generated using them, a relatively small value of tau is needed, rendering the computational costs comparable to Gillespie’s direct method. The multi-level Monte Carlo method (Anderson and Higham, Multiscale Model. Simul. 10:146–179, 2012) provides a reduction in computational costs whilst minimising or even eliminating the bias in the estimates of system statistics. This is achieved by first crudely approximating required statistics with many sample paths of low accuracy. Then correction terms are added until a required level of accuracy is reached. Recent literature has primarily focussed on implementing the multi-level method efficiently to estimate a single system statistic. However, it is clearly also of interest to be able to approximate entire probability distributions of species counts. We present two novel methods that combine known techniques for distribution reconstruction with the multi-level method. We demonstrate the potential of our methods using a number of examples.
Multi-level methods and approximating distribution functions
Energy Technology Data Exchange (ETDEWEB)
Wilson, D., E-mail: daniel.wilson@dtc.ox.ac.uk; Baker, R. E. [Mathematical Institute, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG (United Kingdom)
2016-07-15
Biochemical reaction networks are often modelled using discrete-state, continuous-time Markov chains. System statistics of these Markov chains usually cannot be calculated analytically and therefore estimates must be generated via simulation techniques. There is a well documented class of simulation techniques known as exact stochastic simulation algorithms, an example of which is Gillespie’s direct method. These algorithms often come with high computational costs, therefore approximate stochastic simulation algorithms such as the tau-leap method are used. However, in order to minimise the bias in the estimates generated using them, a relatively small value of tau is needed, rendering the computational costs comparable to Gillespie’s direct method. The multi-level Monte Carlo method (Anderson and Higham, Multiscale Model. Simul. 10:146–179, 2012) provides a reduction in computational costs whilst minimising or even eliminating the bias in the estimates of system statistics. This is achieved by first crudely approximating required statistics with many sample paths of low accuracy. Then correction terms are added until a required level of accuracy is reached. Recent literature has primarily focussed on implementing the multi-level method efficiently to estimate a single system statistic. However, it is clearly also of interest to be able to approximate entire probability distributions of species counts. We present two novel methods that combine known techniques for distribution reconstruction with the multi-level method. We demonstrate the potential of our methods using a number of examples.
Optimal and Approximate Approaches for Deployment of Heterogeneous Sensing Devices
Directory of Open Access Journals (Sweden)
Rabie Ramadan
2007-04-01
Full Text Available A modeling framework for the problem of deploying a set of heterogeneous sensors in a field with time-varying differential surveillance requirements is presented. The problem is formulated as mixed integer mathematical program with the objective to maximize coverage of a given field. Two metaheuristics are used to solve this problem. The first heuristic adopts a genetic algorithm (GA approach while the second heuristic implements a simulated annealing (SA algorithm. A set of experiments is used to illustrate the capabilities of the developed models and to compare their performance. The experiments investigate the effect of parameters related to the size of the sensor deployment problem including number of deployed sensors, size of the monitored field, and length of the monitoring horizon. They also examine several endogenous parameters related to the developed GA and SA algorithms.
Directory of Open Access Journals (Sweden)
Jie Shen
2015-01-01
Full Text Available We describe an extension of the redistributed technique form classical proximal bundle method to the inexact situation for minimizing nonsmooth nonconvex functions. The cutting-planes model we construct is not the approximation to the whole nonconvex function, but to the local convexification of the approximate objective function, and this kind of local convexification is modified dynamically in order to always yield nonnegative linearization errors. Since we only employ the approximate function values and approximate subgradients, theoretical convergence analysis shows that an approximate stationary point or some double approximate stationary point can be obtained under some mild conditions.
Approximate scattering wave functions for few-particle continua
International Nuclear Information System (INIS)
Briggs, J.S.
1990-01-01
An operator identity which allows the wave operator for N particles interacting pairwise to be expanded as products of operators in which fewer than N particles interact is given. This identity is used to derive appproximate scattering wave functions for N-particle continua that avoid certain difficulties associated with Faddeev-type expansions. For example, a derivation is given of a scattering wave function used successfully recently to describe the three-particle continuum occurring in the electron impact ionization of the hydrogen atom
Hermite-Pade approximation approach to hydromagnetic flows in convergent-divergent channels
International Nuclear Information System (INIS)
Makinde, O.D.
2005-10-01
The problem of two-dimensional, steady, nonlinear flow of an incompressible conducting viscous fluid in convergent-divergent channels under the influence of an externally applied homogeneous magnetic field is studied using a special type of Hermite-Pade approximation approach. This semi-numerical scheme offers some advantages over solutions obtained by using traditional methods such as finite differences, spectral method, shooting method, etc. It reveals the analytical structure of the solution function and the important properties of overall flow structure including velocity field, flow reversal control and bifurcations are discussed. (author)
Bisetti, Fabrizio
2012-06-01
Recent trends in hydrocarbon fuel research indicate that the number of species and reactions in chemical kinetic mechanisms is rapidly increasing in an effort to provide predictive capabilities for fuels of practical interest. In order to cope with the computational cost associated with the time integration of stiff, large chemical systems, a novel approach is proposed. The approach combines an exponential integrator and Krylov subspace approximations to the exponential function of the Jacobian matrix. The components of the approach are described in detail and applied to the ignition of stoichiometric methane-air and iso-octane-air mixtures, here described by two widely adopted chemical kinetic mechanisms. The approach is found to be robust even at relatively large time steps and the global error displays a nominal third-order convergence. The performance of the approach is improved by utilising an adaptive algorithm for the selection of the Krylov subspace size, which guarantees an approximation to the matrix exponential within user-defined error tolerance. The Krylov projection of the Jacobian matrix onto a low-dimensional space is interpreted as a local model reduction with a well-defined error control strategy. Finally, the performance of the approach is discussed with regard to the optimal selection of the parameters governing the accuracy of its individual components. © 2012 Copyright Taylor and Francis Group, LLC.
Approximate formulas for elasticity of the Tornquist functions and some their advantages
Issin, Meyram
2017-09-01
In this article functions of demand for prime necessity, second necessity and luxury goods depending on the income are considered. These functions are called Tornquist functions. By means of the return model the demand for prime necessity goods and second necessity goods are approximately described. Then on the basis of a method of the smallest squares approximate formulas for elasticity of these Tornquist functions are received. To receive an approximate formula for elasticity of function of demand for luxury goods, the linear asymptotic formula is constructed for this function. Some benefits of approximate formulas for elasticity of Tornquist functions are specified.
Bayesian Parameter Estimation via Filtering and Functional Approximations
Matthies, Hermann G.
2016-11-25
The inverse problem of determining parameters in a model by comparing some output of the model with observations is addressed. This is a description for what hat to be done to use the Gauss-Markov-Kalman filter for the Bayesian estimation and updating of parameters in a computational model. This is a filter acting on random variables, and while its Monte Carlo variant --- the Ensemble Kalman Filter (EnKF) --- is fairly straightforward, we subsequently only sketch its implementation with the help of functional representations.
Bayesian Parameter Estimation via Filtering and Functional Approximations
Matthies, Hermann G.; Litvinenko, Alexander; Rosic, Bojana V.; Zander, Elmar
2016-01-01
The inverse problem of determining parameters in a model by comparing some output of the model with observations is addressed. This is a description for what hat to be done to use the Gauss-Markov-Kalman filter for the Bayesian estimation and updating of parameters in a computational model. This is a filter acting on random variables, and while its Monte Carlo variant --- the Ensemble Kalman Filter (EnKF) --- is fairly straightforward, we subsequently only sketch its implementation with the help of functional representations.
On Approximation of Hyper-geometric Function Values of a Special Class
Directory of Open Access Journals (Sweden)
P. L. Ivankov
2017-01-01
Full Text Available Investigations of arithmetic properties of the hyper-geometric function values make it possible to single out two trends, namely, Siegel’s method and methods based on the effective construction of a linear approximating form. There are also methods combining both approaches mentioned. The Siegel’s method allows obtaining the most general results concerning the abovementioned problems. In many cases it was used to establish the algebraic independence of the values of corresponding functions. Although the effective methods do not allow obtaining propositions of such generality they have nevertheless some advantages. Among these advantages one can distinguish at least two: a higher precision of the quantitative results obtained by effective methods and a possibility to study the hyper-geometric functions with irrational parameters.In this paper we apply the effective construction to estimate a measure of the linear independence of the hyper-geometric function values over the imaginary quadratic field. The functions themselves were chosen by a special way so that it could be possible to demonstrate a new approach to the effective construction of a linear approximating form. This approach makes it possible also to extend the well-known effective construction methods of the linear approximating forms for poly-logarithms to the functions of more general type.To obtain the arithmetic result we had to establish a linear independence of the functions under consideration over the field of rational functions. It is apparently impossible to apply directly known theorems containing sufficient (and in some cases needful and sufficient conditions for the system of functions appearing in the theorems mentioned. For this reason, a special technique has been developed to solve this problem.The paper presents the obtained arithmetic results concerning the values of integral functions, but, with appropriate alterations, the theorems proved can be adapted to
International Nuclear Information System (INIS)
Cafiero, Mauricio; Gonzalez, Carlos
2005-01-01
We show that potentials for exchange-correlation functionals within the Kohn-Sham density-functional-theory framework may be written as potentials for simpler functionals multiplied by a factor close to unity, and in a self-consistent field calculation, these effective potentials find the correct self-consistent solutions. This simple theory is demonstrated with self-consistent exchange-only calculations of the atomization energies of some small molecules using the Perdew-Kurth-Zupan-Blaha (PKZB) meta-generalized-gradient-approximation (meta-GGA) exchange functional. The atomization energies obtained with our method agree with or surpass previous meta-GGA calculations performed in a non-self-consistent manner. The results of this work suggest the utility of this simple theory to approximate exchange-correlation potentials corresponding to energy functionals too complicated to generate closed forms for their potentials. We hope that this method will encourage the development of complex functionals which have correct boundary conditions and are free of self-interaction errors without the worry that the functionals are too complex to differentiate to obtain potentials
Approximating Smooth Step Functions Using Partial Fourier Series Sums
2012-09-01
interp1(xt(ii), smoothstepbez( t(ii), min(t(ii)), max(t(ii)), ’y’), t(ii), ’linear’, ’ extrap ’); ii = find( abs(t - tau/2) <= epi ); iii = t(ii...interp1( xt(ii), smoothstepbez( rt, min(rt), max(rt), ’y’), t(ii), ’linear’, ’ extrap ’ ); % stepm(ii) = 1 - interp1(xt(ii), smoothstepbez( t(ii...min(t(ii)), max(t(ii)), ’y’), t(ii), ’linear’, ’ extrap ’); In this case, because x is also defined as a function of the independent parameter
Approximate relativistic corrections to atomic radial wave functions
International Nuclear Information System (INIS)
Cowan, R.D.; Griffin, D.C.
1976-01-01
The mass-velocity and Darwin terms of the one-electron-atom Pauli equation have been added to the Hartree-Fock differential equations by using the HX formula to calculate a local central field potential for use in these terms. Introduction of the quantum number j is avoided by omitting the spin-orbit term of the Pauli equation. The major relativistic effects, both direct and indirect, are thereby incorporated into the wave functions, while allowing retention of the commonly used nonrelativistic formulation of energy level calculations. The improvement afforded in calculated total binding energies, excitation energies, spin-orbit parameters, and expectation values of r/sub m/ is comparable with that provided by fully relativistic Dirac-Hartree-Fock calculations
The approximation function of bridge deck vibration derived from the measured eigenmodes
Directory of Open Access Journals (Sweden)
Sokol Milan
2017-12-01
Full Text Available This article deals with a method of how to acquire approximate displacement vibration functions. Input values are discrete, experimentally obtained mode shapes. A new improved approximation method based on the modal vibrations of the deck is derived using the least-squares method. An alternative approach to be employed in this paper is to approximate the displacement vibration function by a sum of sine functions whose periodicity is determined by spectral analysis adapted for non-uniformly sampled data and where the parameters of scale and phase are estimated as usual by the least-squares method. Moreover, this periodic component is supplemented by a cubic regression spline (fitted on its residuals that captures individual displacements between piers. The statistical evaluation of the stiffness parameter is performed using more vertical modes obtained from experimental results. The previous method (Sokol and Flesch, 2005, which was derived for near the pier areas, has been enhanced to the whole length of the bridge. The experimental data describing the mode shapes are not appropriate for direct use. Especially the higher derivatives calculated from these data are very sensitive to data precision.
Analytic approximation for the modified Bessel function I -2/3(x)
Martin, Pablo; Olivares, Jorge; Maass, Fernando
2017-12-01
In the present work an analytic approximation to modified Bessel function of negative fractional order I -2/3(x) is presented. The validity of the approximation is for every positive value of the independent variable. The accuracy is high in spite of the small number (4) of parameters used. The approximation is a combination of elementary functions with rational ones. Power series and assymptotic expansions are simultaneously used to obtain the approximation.
Energy Technology Data Exchange (ETDEWEB)
Druskin, V.; Lee, Ping [Schlumberger-Doll Research, Ridgefield, CT (United States); Knizhnerman, L. [Central Geophysical Expedition, Moscow (Russian Federation)
1996-12-31
There is now a growing interest in the area of using Krylov subspace approximations to compute the actions of matrix functions. The main application of this approach is the solution of ODE systems, obtained after discretization of partial differential equations by method of lines. In the event that the cost of computing the matrix inverse is relatively inexpensive, it is sometimes attractive to solve the ODE using the extended Krylov subspaces, originated by actions of both positive and negative matrix powers. Examples of such problems can be found frequently in computational electromagnetics.
Long-range-corrected Rung 3.5 density functional approximations
Janesko, Benjamin G.; Proynov, Emil; Scalmani, Giovanni; Frisch, Michael J.
2018-03-01
Rung 3.5 functionals are a new class of approximations for density functional theory. They provide a flexible intermediate between exact (Hartree-Fock, HF) exchange and semilocal approximations for exchange. Existing Rung 3.5 functionals inherit semilocal functionals' limitations in atomic cores and density tails. Here we address those limitations using range-separated admixture of HF exchange. We present three new functionals. LRC-ωΠLDA combines long-range HF exchange with short-range Rung 3.5 ΠLDA exchange. SLC-ΠLDA combines short- and long-range HF exchange with middle-range ΠLDA exchange. LRC-ωΠLDA-AC incorporates a combination of HF, semilocal, and Rung 3.5 exchange in the short range, based on an adiabatic connection. We test these in a new Rung 3.5 implementation including up to analytic fourth derivatives. LRC-ωΠLDA and SLC-ΠLDA improve atomization energies and reaction barriers by a factor of 8 compared to the full-range ΠLDA. LRC-ωΠLDA-AC brings further improvement approaching the accuracy of standard long-range corrected schemes LC-ωPBE and SLC-PBE. The new functionals yield highest occupied orbital energies closer to experimental ionization potentials and describe correctly the weak charge-transfer complex of ethylene and dichlorine and the hole-spin distribution created by an Al defect in quartz. This study provides a framework for more flexible range-separated Rung 3.5 approximations.
Integration a functional approach
Bichteler, Klaus
1998-01-01
This book covers Lebesgue integration and its generalizations from Daniell's point of view, modified by the use of seminorms. Integrating functions rather than measuring sets is posited as the main purpose of measure theory. From this point of view Lebesgue's integral can be had as a rather straightforward, even simplistic, extension of Riemann's integral; and its aims, definitions, and procedures can be motivated at an elementary level. The notion of measurability, for example, is suggested by Littlewood's observations rather than being conveyed authoritatively through definitions of (sigma)-algebras and good-cut-conditions, the latter of which are hard to justify and thus appear mysterious, even nettlesome, to the beginner. The approach taken provides the additional benefit of cutting the labor in half. The use of seminorms, ubiquitous in modern analysis, speeds things up even further. The book is intended for the reader who has some experience with proofs, a beginning graduate student for example. It might...
Energy Technology Data Exchange (ETDEWEB)
Kotelnikova, O.A.; Prudnikov, V.N. [Physical Faculty, Lomonosov State University, Department of Magnetism, Moscow (Russian Federation); Rudoy, Yu.G., E-mail: rudikar@mail.ru [People' s Friendship University of Russia, Department of Theoretical Physics, Moscow (Russian Federation)
2015-06-01
The aim of this paper is to generalize the microscopic approach to the description of the magnetocaloric effect (MCE) started by Kokorina and Medvedev (E.E. Kokorina, M.V. Medvedev, Physica B 416 (2013) 29.) by applying it to the anisotropic ferromagnet of the “easy axis” type in two settings—with external magnetic field parallel and perpendicular to the axis of easy magnetization. In the last case there appears the field induced (or spin-reorientation) phase transition which occurs at the critical value of the external magnetic field. This value is proportional to the exchange anisotropy constant at low temperatures, but with the rise of temperature it may be renormalized (as a rule, proportional to the magnetization). We use the explicit form of the Hamiltonian of the anisotropic ferromagnet and apply widely used random phase approximation (RPA) (known also as Tyablikov approximation in the Green function method) which is more accurate than the well known molecular field approximation (MFA). It is shown that in the first case the magnitude of MCE is raised whereas in the second one the MCE disappears due to compensation of the critical field renormalized with the magnetization.
High-Dimensional Function Approximation With Neural Networks for Large Volumes of Data.
Andras, Peter
2018-02-01
Approximation of high-dimensional functions is a challenge for neural networks due to the curse of dimensionality. Often the data for which the approximated function is defined resides on a low-dimensional manifold and in principle the approximation of the function over this manifold should improve the approximation performance. It has been show that projecting the data manifold into a lower dimensional space, followed by the neural network approximation of the function over this space, provides a more precise approximation of the function than the approximation of the function with neural networks in the original data space. However, if the data volume is very large, the projection into the low-dimensional space has to be based on a limited sample of the data. Here, we investigate the nature of the approximation error of neural networks trained over the projection space. We show that such neural networks should have better approximation performance than neural networks trained on high-dimensional data even if the projection is based on a relatively sparse sample of the data manifold. We also find that it is preferable to use a uniformly distributed sparse sample of the data for the purpose of the generation of the low-dimensional projection. We illustrate these results considering the practical neural network approximation of a set of functions defined on high-dimensional data including real world data as well.
International Nuclear Information System (INIS)
Sato, M.
1991-01-01
The Saha equation for a plasma in thermodynamic equilibrium (TE) is approximately solved to give the temperature as an explicit function of population densities. It is shown that the derived expressions for the Saha temperature are valid approximations to the exact solution. An application of the approximate temperature to the calculation of TE plasma parameters is also described. (orig.)
Gorban, A N; Mirkes, E M; Zinovyev, A
2016-12-01
Most of machine learning approaches have stemmed from the application of minimizing the mean squared distance principle, based on the computationally efficient quadratic optimization methods. However, when faced with high-dimensional and noisy data, the quadratic error functionals demonstrated many weaknesses including high sensitivity to contaminating factors and dimensionality curse. Therefore, a lot of recent applications in machine learning exploited properties of non-quadratic error functionals based on L 1 norm or even sub-linear potentials corresponding to quasinorms L p (0application of min-plus algebra. The approach can be applied in most of existing machine learning methods, including methods of data approximation and regularized and sparse regression, leading to the improvement in the computational cost/accuracy trade-off. We demonstrate that on synthetic and real-life datasets PQSQ-based machine learning methods achieve orders of magnitude faster computational performance than the corresponding state-of-the-art methods, having similar or better approximation accuracy. Copyright © 2016 Elsevier Ltd. All rights reserved.
Global Approximations to Cost and Production Functions using Artificial Neural Networks
Directory of Open Access Journals (Sweden)
Efthymios G. Tsionas
2009-06-01
Full Text Available The estimation of cost and production functions in economics relies on standard specifications which are less than satisfactory in numerous situations. However, instead of fitting the data with a pre-specified model, Artificial Neural Networks (ANNs let the data itself serve as evidence to support the modelrs estimation of the underlying process. In this context, the proposed approach combines the strengths of economics, statistics and machine learning research and the paper proposes a global approximation to arbitrary cost and production functions, respectively, given by ANNs. Suggestions on implementation are proposed and empirical application relies on standard techniques. All relevant measures such as Returns to Scale (RTS and Total Factor Productivity (TFP may be computed routinely.
International Nuclear Information System (INIS)
Gaj, E.V.; Badikov, S.A.; Gusejnov, M.A.; Rabotnov, N.S.
1988-01-01
Possible applications of rational functions in the analysis of neutron cross sections, angular distributions and neutron constants generation are described. Results of investigations made in this direction, which have been obtained after the preceding conference in Kiev, are presented: the method of simultaneous treatment of several cross sections for one compound nucleus in the resonance range; the use of the Pade approximation for elastically scattered neutron angular distribution approximation; obtaining of subgroup constants on the basis of rational approximation of cross section functional dependence on dilution cross section; the first experience in function approximation by two variables
A general approach for cache-oblivious range reporting and approximate range counting
DEFF Research Database (Denmark)
Afshani, Peyman; Hamilton, Chris; Zeh, Norbert
2010-01-01
We present cache-oblivious solutions to two important variants of range searching: range reporting and approximate range counting. Our main contribution is a general approach for constructing cache-oblivious data structures that provide relative (1+ε)-approximations for a general class of range c...
Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach.
Ramakrishnan, Raghunathan; Dral, Pavlo O; Rupp, Matthias; von Lilienfeld, O Anatole
2015-05-12
Chemically accurate and comprehensive studies of the virtual space of all possible molecules are severely limited by the computational cost of quantum chemistry. We introduce a composite strategy that adds machine learning corrections to computationally inexpensive approximate legacy quantum methods. After training, highly accurate predictions of enthalpies, free energies, entropies, and electron correlation energies are possible, for significantly larger molecular sets than used for training. For thermochemical properties of up to 16k isomers of C7H10O2 we present numerical evidence that chemical accuracy can be reached. We also predict electron correlation energy in post Hartree-Fock methods, at the computational cost of Hartree-Fock, and we establish a qualitative relationship between molecular entropy and electron correlation. The transferability of our approach is demonstrated, using semiempirical quantum chemistry and machine learning models trained on 1 and 10% of 134k organic molecules, to reproduce enthalpies of all remaining molecules at density functional theory level of accuracy.
An Approximate Proximal Bundle Method to Minimize a Class of Maximum Eigenvalue Functions
Directory of Open Access Journals (Sweden)
Wei Wang
2014-01-01
Full Text Available We present an approximate nonsmooth algorithm to solve a minimization problem, in which the objective function is the sum of a maximum eigenvalue function of matrices and a convex function. The essential idea to solve the optimization problem in this paper is similar to the thought of proximal bundle method, but the difference is that we choose approximate subgradient and function value to construct approximate cutting-plane model to solve the above mentioned problem. An important advantage of the approximate cutting-plane model for objective function is that it is more stable than cutting-plane model. In addition, the approximate proximal bundle method algorithm can be given. Furthermore, the sequences generated by the algorithm converge to the optimal solution of the original problem.
Approximation Of Multi-Valued Inverse Functions Using Clustering And Sugeno Fuzzy Inference
Walden, Maria A.; Bikdash, Marwan; Homaifar, Abdollah
1998-01-01
Finding the inverse of a continuous function can be challenging and computationally expensive when the inverse function is multi-valued. Difficulties may be compounded when the function itself is difficult to evaluate. We show that we can use fuzzy-logic approximators such as Sugeno inference systems to compute the inverse on-line. To do so, a fuzzy clustering algorithm can be used in conjunction with a discriminating function to split the function data into branches for the different values of the forward function. These data sets are then fed into a recursive least-squares learning algorithm that finds the proper coefficients of the Sugeno approximators; each Sugeno approximator finds one value of the inverse function. Discussions about the accuracy of the approximation will be included.
Shiju, S.; Sumitra, S.
2017-12-01
In this paper, the multiple kernel learning (MKL) is formulated as a supervised classification problem. We dealt with binary classification data and hence the data modelling problem involves the computation of two decision boundaries of which one related with that of kernel learning and the other with that of input data. In our approach, they are found with the aid of a single cost function by constructing a global reproducing kernel Hilbert space (RKHS) as the direct sum of the RKHSs corresponding to the decision boundaries of kernel learning and input data and searching that function from the global RKHS, which can be represented as the direct sum of the decision boundaries under consideration. In our experimental analysis, the proposed model had shown superior performance in comparison with that of existing two stage function approximation formulation of MKL, where the decision functions of kernel learning and input data are found separately using two different cost functions. This is due to the fact that single stage representation helps the knowledge transfer between the computation procedures for finding the decision boundaries of kernel learning and input data, which inturn boosts the generalisation capacity of the model.
International Nuclear Information System (INIS)
Galatolo, Stefano; Monge, Maurizio; Nisoli, Isaia
2016-01-01
We study the problem of the rigorous computation of the stationary measure and of the rate of convergence to equilibrium of an iterated function system described by a stochastic mixture of two or more dynamical systems that are either all uniformly expanding on the interval, either all contracting. In the expanding case, the associated transfer operators satisfy a Lasota–Yorke inequality, we show how to compute a rigorous approximations of the stationary measure in the L "1 norm and an estimate for the rate of convergence. The rigorous computation requires a computer-aided proof of the contraction of the transfer operators for the maps, and we show that this property propagates to the transfer operators of the IFS. In the contracting case we perform a rigorous approximation of the stationary measure in the Wasserstein–Kantorovich distance and rate of convergence, using the same functional analytic approach. We show that a finite computation can produce a realistic computation of all contraction rates for the whole parameter space. We conclude with a description of the implementation and numerical experiments. (paper)
International Nuclear Information System (INIS)
Wyatt, Robert E.; Kouri, Donald J.; Hoffman, David K.
2000-01-01
The quantum trajectory method (QTM) was recently developed to solve the hydrodynamic equations of motion in the Lagrangian, moving-with-the-fluid, picture. In this approach, trajectories are integrated for N fluid elements (particles) moving under the influence of both the force from the potential surface and from the quantum potential. In this study, distributed approximating functionals (DAFs) are used on a uniform grid to compute the necessary derivatives in the equations of motion. Transformations between the physical grid where the particle coordinates are defined and the uniform grid are handled through a Jacobian, which is also computed using DAFs. A difficult problem associated with computing derivatives on finite grids is the edge problem. This is handled effectively by using DAFs within a least squares approach to extrapolate from the known function region into the neighboring regions. The QTM-DAF is then applied to wave packet transmission through a one-dimensional Eckart potential. Emphasis is placed upon computation of the transmitted density and wave function. A problem that develops when part of the wave packet reflects back into the reactant region is avoided in this study by introducing a potential ramp to sweep the reflected particles away from the barrier region. (c) 2000 American Institute of Physics
International Nuclear Information System (INIS)
Marrero, S. I.; Turibus, S. N.; Assis, J. T. De; Monin, V. I.
2011-01-01
Data processing of the most of diffraction experiments is based on determination of diffraction line position and measurement of broadening of diffraction profile. High precision and digitalisation of these procedures can be resolved by approximation of experimental diffraction profiles by analytical functions. There are various functions for these purposes both simples, like Gauss function, but no suitable for wild range of experimental profiles and good approximating functions but complicated for practice using, like Vougt or PersonVII functions. Proposed analytical function is modified Cauchy function which uses two variable parameters allowing describing any experimental diffraction profile. In the presented paper modified function was applied for approximation of diffraction lines of steels after various physical and mechanical treatments and simulation of diffraction profiles applied for study of stress gradients and distortions of crystal structure. (Author)
A new way of obtaining analytic approximations of Chandrasekhar's H function
International Nuclear Information System (INIS)
Vukanic, J.; Arsenovic, D.; Davidovic, D.
2007-01-01
Applying the mean value theorem for definite integrals in the non-linear integral equation for Chandrasekhar's H function describing conservative isotropic scattering, we have derived a new, simple analytic approximation for it, with a maximal relative error below 2.5%. With this new function as a starting-point, after a single iteration in the corresponding integral equation, we have obtained a new, highly accurate analytic approximation for the H function. As its maximal relative error is below 0.07%, it significantly surpasses the accuracy of other analytic approximations
International Nuclear Information System (INIS)
Ramazanov, A.-R K
2005-01-01
Necessary and sufficient conditions for the best polynomial approximation with an arbitrary and, generally speaking, unbounded sign-sensitive weight to a continuous function are obtained; the components of the weight can also take infinite values, therefore the conditions obtained cover, in particular, approximation with interpolation at fixed points and one-sided approximation; in the case of the weight with components equal to 1 one arrives at Chebyshev's classical alternation theorem.
density functional theory approach
Indian Academy of Sciences (India)
YOGESH ERANDE
2017-07-27
Jul 27, 2017 ... a key role in all optical switching devices, since their optical properties can be .... optimized in the gas phase using Density Functional Theory. (DFT).39 The ...... The Mediation of Electrostatic Effects by Sol- vents J. Am. Chem.
Frolov, Maxim; Chistiakova, Olga
2017-06-01
Paper is devoted to a numerical justification of the recent a posteriori error estimate for Reissner-Mindlin plates. This majorant provides a reliable control of accuracy of any conforming approximate solution of the problem including solutions obtained with commercial software for mechanical engineering. The estimate is developed on the basis of the functional approach and is applicable to several types of boundary conditions. To verify the approach, numerical examples with mesh refinements are provided.
Directory of Open Access Journals (Sweden)
W. Łenski
2015-01-01
Full Text Available The results generalizing some theorems on N, pnE, γ summability are shown. The same degrees of pointwise approximation as in earlier papers by weaker assumptions on considered functions and examined summability methods are obtained. From presented pointwise results, the estimation on norm approximation is derived. Some special cases as corollaries are also formulated.
Delta-function Approximation SSC Model in 3C 273 S. J. Kang1 ...
Indian Academy of Sciences (India)
Abstract. We obtain an approximate analytical solution using δ approximate calculation on the traditional one-zone synchrotron self-. Compton (SSC) model. In this model, we describe the electron energy distribution by a broken power-law function with a sharp cut-off, and non- thermal photons are produced by both ...
Towards the Accuracy of Cybernetic Strategy Planning Models: Causal Proof and Function Approximation
Directory of Open Access Journals (Sweden)
Christian A. Hillbrand
2003-04-01
Full Text Available All kind of strategic tasks within an enterprise require a deep understanding of its critical key success factors and their interrelations as well as an in-depth analysis of relevant environmental influences. Due to the openness of the underlying system, there seems to be an indefinite number of unknown variables influencing strategic goals. Cybernetic or systemic planning techniques try to overcome this intricacy by modeling the most important cause-and-effect relations within such a system. Although it seems to be obvious that there are specific influences between business variables, it is mostly impossible to identify the functional dependencies underlying such relations. Hence simulation or evaluation techniques based on such hypothetically assumed models deliver inaccurate results or fail completely. This paper addresses the need for accurate strategy planning models and proposes an approach to prove their cause-andeffect relations by empirical evidence. Based on this foundation an approach for the approximation of the underlying cause-andeffect function by the means of Artificial Neural Networks is developed.
Leibov Roman
2017-01-01
This paper presents a bilinear approach to nonlinear differential equations system approximation problem. Sometimes the nonlinear differential equations right-hand sides linearization is extremely difficult or even impossible. Then piecewise-linear approximation of nonlinear differential equations can be used. The bilinear differential equations allow to improve piecewise-linear differential equations behavior and reduce errors on the border of different linear differential equations systems ...
Merging Belief Propagation and the Mean Field Approximation: A Free Energy Approach
DEFF Research Database (Denmark)
Riegler, Erwin; Kirkelund, Gunvor Elisabeth; Manchón, Carles Navarro
2013-01-01
We present a joint message passing approach that combines belief propagation and the mean field approximation. Our analysis is based on the region-based free energy approximation method proposed by Yedidia et al. We show that the message passing fixed-point equations obtained with this combination...... correspond to stationary points of a constrained region-based free energy approximation. Moreover, we present a convergent implementation of these message passing fixed-point equations provided that the underlying factor graph fulfills certain technical conditions. In addition, we show how to include hard...
Approximation of functions in two variables by some linear positive operators
Directory of Open Access Journals (Sweden)
Mariola Skorupka
1995-12-01
Full Text Available We introduce some linear positive operators of the Szasz-Mirakjan type in the weighted spaces of continuous functions in two variables. We study the degree of the approximation of functions by these operators. The similar results for functions in one variable are given in [5]. Some operators of the Szasz-Mirakjan type are examined also in [3], [4].
National Research Council Canada - National Science Library
Franke, Richard
2001-01-01
.... It was found that for all levels the approximation of the covariance data for pressure height innovations by Legendre functions led to positive coefficients for up to 25 terms except at the some low and high levels...
International Nuclear Information System (INIS)
Capelle, K.; Gross, E.
1997-01-01
It is shown that the exchange-correlation functional of spin-density functional theory is identical, on a certain set of densities, with the exchange-correlation functional of current-density functional theory. This rigorous connection is used to construct new approximations of the exchange-correlation functionals. These include a conceptually new generalized-gradient spin-density functional and a nonlocal current-density functional. copyright 1997 The American Physical Society
Narimani, Mohammand; Lam, H K; Dilmaghani, R; Wolfe, Charles
2011-06-01
Relaxed linear-matrix-inequality-based stability conditions for fuzzy-model-based control systems with imperfect premise matching are proposed. First, the derivative of the Lyapunov function, containing the product terms of the fuzzy model and fuzzy controller membership functions, is derived. Then, in the partitioned operating domain of the membership functions, the relations between the state variables and the mentioned product terms are represented by approximated polynomials in each subregion. Next, the stability conditions containing the information of all subsystems and the approximated polynomials are derived. In addition, the concept of the S-procedure is utilized to release the conservativeness caused by considering the whole operating region for approximated polynomials. It is shown that the well-known stability conditions can be special cases of the proposed stability conditions. Simulation examples are given to illustrate the validity of the proposed approach.
Kushwaha, Jitendra Kumar
2013-01-01
Approximation theory is a very important field which has various applications in pure and applied mathematics. The present study deals with a new theorem on the approximation of functions of Lipschitz class by using Euler's mean of conjugate series of Fourier series. In this paper, the degree of approximation by using Euler's means of conjugate of functions belonging to Lip (ξ(t), p) class has been obtained. Lipα and Lip (α, p) classes are the particular cases of Lip (ξ(t), p) class. The main result of this paper generalizes some well-known results in this direction. PMID:24379744
Monotone Approximations of Minimum and Maximum Functions and Multi-objective Problems
International Nuclear Information System (INIS)
Stipanović, Dušan M.; Tomlin, Claire J.; Leitmann, George
2012-01-01
In this paper the problem of accomplishing multiple objectives by a number of agents represented as dynamic systems is considered. Each agent is assumed to have a goal which is to accomplish one or more objectives where each objective is mathematically formulated using an appropriate objective function. Sufficient conditions for accomplishing objectives are derived using particular convergent approximations of minimum and maximum functions depending on the formulation of the goals and objectives. These approximations are differentiable functions and they monotonically converge to the corresponding minimum or maximum function. Finally, an illustrative pursuit-evasion game example with two evaders and two pursuers is provided.
Monotone Approximations of Minimum and Maximum Functions and Multi-objective Problems
Energy Technology Data Exchange (ETDEWEB)
Stipanovic, Dusan M., E-mail: dusan@illinois.edu [University of Illinois at Urbana-Champaign, Coordinated Science Laboratory, Department of Industrial and Enterprise Systems Engineering (United States); Tomlin, Claire J., E-mail: tomlin@eecs.berkeley.edu [University of California at Berkeley, Department of Electrical Engineering and Computer Science (United States); Leitmann, George, E-mail: gleit@berkeley.edu [University of California at Berkeley, College of Engineering (United States)
2012-12-15
In this paper the problem of accomplishing multiple objectives by a number of agents represented as dynamic systems is considered. Each agent is assumed to have a goal which is to accomplish one or more objectives where each objective is mathematically formulated using an appropriate objective function. Sufficient conditions for accomplishing objectives are derived using particular convergent approximations of minimum and maximum functions depending on the formulation of the goals and objectives. These approximations are differentiable functions and they monotonically converge to the corresponding minimum or maximum function. Finally, an illustrative pursuit-evasion game example with two evaders and two pursuers is provided.
Correlation energy functional within the GW -RPA: Exact forms, approximate forms, and challenges
Ismail-Beigi, Sohrab
2010-05-01
In principle, the Luttinger-Ward Green’s-function formalism allows one to compute simultaneously the total energy and the quasiparticle band structure of a many-body electronic system from first principles. We present approximate and exact expressions for the correlation energy within the GW -random-phase approximation that are more amenable to computation and allow for developing efficient approximations to the self-energy operator and correlation energy. The exact form is a sum over differences between plasmon and interband energies. The approximate forms are based on summing over screened interband transitions. We also demonstrate that blind extremization of such functionals leads to unphysical results: imposing physical constraints on the allowed solutions (Green’s functions) is necessary. Finally, we present some relevant numerical results for atomic systems.
Bronstein, Leo; Koeppl, Heinz
2018-01-01
Approximate solutions of the chemical master equation and the chemical Fokker-Planck equation are an important tool in the analysis of biomolecular reaction networks. Previous studies have highlighted a number of problems with the moment-closure approach used to obtain such approximations, calling it an ad hoc method. In this article, we give a new variational derivation of moment-closure equations which provides us with an intuitive understanding of their properties and failure modes and allows us to correct some of these problems. We use mixtures of product-Poisson distributions to obtain a flexible parametric family which solves the commonly observed problem of divergences at low system sizes. We also extend the recently introduced entropic matching approach to arbitrary ansatz distributions and Markov processes, demonstrating that it is a special case of variational moment closure. This provides us with a particularly principled approximation method. Finally, we extend the above approaches to cover the approximation of multi-time joint distributions, resulting in a viable alternative to process-level approximations which are often intractable.
Optimized implementations of rational approximations for the Voigt and complex error function
International Nuclear Information System (INIS)
Schreier, Franz
2011-01-01
Rational functions are frequently used as efficient yet accurate numerical approximations for real and complex valued functions. For the complex error function w(x+iy), whose real part is the Voigt function K(x,y), code optimizations of rational approximations are investigated. An assessment of requirements for atmospheric radiative transfer modeling indicates a y range over many orders of magnitude and accuracy better than 10 -4 . Following a brief survey of complex error function algorithms in general and rational function approximations in particular the problems associated with subdivisions of the x, y plane (i.e., conditional branches in the code) are discussed and practical aspects of Fortran and Python implementations are considered. Benchmark tests of a variety of algorithms demonstrate that programming language, compiler choice, and implementation details influence computational speed and there is no unique ranking of algorithms. A new implementation, based on subdivision of the upper half-plane in only two regions, combining Weideman's rational approximation for small |x|+y<15 and Humlicek's rational approximation otherwise is shown to be efficient and accurate for all x, y.
Pan, Zhen; Anderes, Ethan; Knox, Lloyd
2018-05-01
One of the major targets for next-generation cosmic microwave background (CMB) experiments is the detection of the primordial B-mode signal. Planning is under way for Stage-IV experiments that are projected to have instrumental noise small enough to make lensing and foregrounds the dominant source of uncertainty for estimating the tensor-to-scalar ratio r from polarization maps. This makes delensing a crucial part of future CMB polarization science. In this paper we present a likelihood method for estimating the tensor-to-scalar ratio r from CMB polarization observations, which combines the benefits of a full-scale likelihood approach with the tractability of the quadratic delensing technique. This method is a pixel space, all order likelihood analysis of the quadratic delensed B modes, and it essentially builds upon the quadratic delenser by taking into account all order lensing and pixel space anomalies. Its tractability relies on a crucial factorization of the pixel space covariance matrix of the polarization observations which allows one to compute the full Gaussian approximate likelihood profile, as a function of r , at the same computational cost of a single likelihood evaluation.
A point-value enhanced finite volume method based on approximate delta functions
Xuan, Li-Jun; Majdalani, Joseph
2018-02-01
We revisit the concept of an approximate delta function (ADF), introduced by Huynh (2011) [1], in the form of a finite-order polynomial that holds identical integral properties to the Dirac delta function when used in conjunction with a finite-order polynomial integrand over a finite domain. We show that the use of generic ADF polynomials can be effective at recovering and generalizing several high-order methods, including Taylor-based and nodal-based Discontinuous Galerkin methods, as well as the Correction Procedure via Reconstruction. Based on the ADF concept, we then proceed to formulate a Point-value enhanced Finite Volume (PFV) method, which stores and updates the cell-averaged values inside each element as well as the unknown quantities and, if needed, their derivatives on nodal points. The sharing of nodal information with surrounding elements saves the number of degrees of freedom compared to other compact methods at the same order. To ensure conservation, cell-averaged values are updated using an identical approach to that adopted in the finite volume method. Here, the updating of nodal values and their derivatives is achieved through an ADF concept that leverages all of the elements within the domain of integration that share the same nodal point. The resulting scheme is shown to be very stable at successively increasing orders. Both accuracy and stability of the PFV method are verified using a Fourier analysis and through applications to the linear wave and nonlinear Burgers' equations in one-dimensional space.
Many-body perturbation theory using the density-functional concept: beyond the GW approximation.
Bruneval, Fabien; Sottile, Francesco; Olevano, Valerio; Del Sole, Rodolfo; Reining, Lucia
2005-05-13
We propose an alternative formulation of many-body perturbation theory that uses the density-functional concept. Instead of the usual four-point integral equation for the polarizability, we obtain a two-point one, which leads to excellent optical absorption and energy-loss spectra. The corresponding three-point vertex function and self-energy are then simply calculated via an integration, for any level of approximation. Moreover, we show the direct impact of this formulation on the time-dependent density-functional theory. Numerical results for the band gap of bulk silicon and solid argon illustrate corrections beyond the GW approximation for the self-energy.
Physical Applications of a Simple Approximation of Bessel Functions of Integer Order
Barsan, V.; Cojocaru, S.
2007-01-01
Applications of a simple approximation of Bessel functions of integer order, in terms of trigonometric functions, are discussed for several examples from electromagnetism and optics. The method may be applied in the intermediate regime, bridging the "small values regime" and the "asymptotic" one, and covering, in this way, an area of great…
Agarwal, Mukul
2018-01-01
It is proved that the limit of the normalized rate-distortion functions of block independent approximations of an irreducible, aperiodic Markoff chain is independent of the initial distribution of the Markoff chain and thus, is also equal to the rate-distortion function of the Markoff chain.
Local density approximation for exchange in excited-state density functional theory
Harbola, Manoj K.; Samal, Prasanjit
2004-01-01
Local density approximation for the exchange energy is made for treatment of excited-states in density-functional theory. It is shown that taking care of the state-dependence of the LDA exchange energy functional leads to accurate excitation energies.
Bessel harmonic analysis and approximation of functions on the half-line
International Nuclear Information System (INIS)
Platonov, Sergei S
2007-01-01
We study problems of approximation of functions on [0,+∞) in the metric of L p with power weight using generalized Bessel shifts. We prove analogues of direct Jackson theorems for the modulus of smoothness of arbitrary order defined in terms of generalized Bessel shifts. We establish the equivalence of the modulus of smoothness and the K-functional. We define function spaces of Nikol'skii-Besov type and describe them in terms of best approximations. As a tool for approximation, we use a certain class of entire functions of exponential type. In this class, we prove analogues of Bernstein's inequality and others for the Bessel differential operator and its fractional powers. The main tool we use to solve these problems is Bessel harmonic analysis
Numerical analysis of different neural transfer functions used for best approximation
International Nuclear Information System (INIS)
Gougam, L.A.; Chikhi, A.; Biskri, S.; Chafa, F.
2006-01-01
It is widely recognised that the choice of transfer functions in neural networks is of en importance to their performance. In this paper, different neural transfer functions usec approximation are discussed. We begin with sigmoi'dal functions used most often by diffi authors . At a second step, we use Gaussian functions as previously suggested in refere Finally, we deal with a specified wavelet family. A comparison between the three cases < above is made exhibiting therefore the advantages of each transfer function. The approa< function improves as the dimension N of the elementary task basis increases
Elfwing, Stefan; Uchibe, Eiji; Doya, Kenji
2016-12-01
Free-energy based reinforcement learning (FERL) was proposed for learning in high-dimensional state and action spaces. However, the FERL method does only really work well with binary, or close to binary, state input, where the number of active states is fewer than the number of non-active states. In the FERL method, the value function is approximated by the negative free energy of a restricted Boltzmann machine (RBM). In our earlier study, we demonstrated that the performance and the robustness of the FERL method can be improved by scaling the free energy by a constant that is related to the size of network. In this study, we propose that RBM function approximation can be further improved by approximating the value function by the negative expected energy (EERL), instead of the negative free energy, as well as being able to handle continuous state input. We validate our proposed method by demonstrating that EERL: (1) outperforms FERL, as well as standard neural network and linear function approximation, for three versions of a gridworld task with high-dimensional image state input; (2) achieves new state-of-the-art results in stochastic SZ-Tetris in both model-free and model-based learning settings; and (3) significantly outperforms FERL and standard neural network function approximation for a robot navigation task with raw and noisy RGB images as state input and a large number of actions. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.
International Nuclear Information System (INIS)
Lee, M.W.; Bigeleisen, J.
1978-01-01
The MINIMAX finite polynomial approximation to an arbitrary function has been generalized to include a weighting function (WINIMAX). It is suggested that an exponential is a reasonable weighting function for the logarithm of the reduced partition function of a harmonic oscillator. Comparison of the error function for finite orthogonal polynomial (FOP), MINIMAX, and WINIMAX expansions of the logarithm of the reduced vibrational partition function show WINIMAX to be the best of the three approximations. A condensed table of WINIMAX coefficients is presented. The FOP, MINIMAX, and WINIMAX approximations are compared with exact calculations of the logarithm of the reduced partition function ratios for isotopic substitution in H 2 O, CH 4 , CH 2 O, C 2 H 4 , and C 2 H 6 at 300 0 K. Both deuterium and heavy atom isotope substitution are studied. Except for a third order expansion involving deuterium substitution, the WINIMAX method is superior to FOP and MINIMAX. At the level of a second order expansion WINIMAX approximations to ln(s/s')f are good to 2.5% and 6.5% for deuterium and heavy atom substitution, respectively
FUNPACK-2, Subroutine Library, Bessel Function, Elliptical Integrals, Min-max Approximation
International Nuclear Information System (INIS)
Cody, W.J.; Garbow, Burton S.
1975-01-01
1 - Description of problem or function: FUNPACK is a collection of FORTRAN subroutines to evaluate certain special functions. The individual subroutines are (Identification/Description): NATSI0 F2I0 Bessel function I 0 ; NATSI1 F2I1 Bessel function I 1 ; NATSJ0 F2J0 Bessel function J 0 ; NATSJ1 F2J1 Bessel function J 1 ; NATSK0 F2K0 Bessel function K 0 ; NATSK1 F2K1 Bessel function K 1 ; NATSBESY F2BY Bessel function Y ν ; DAW F1DW Dawson's integral; DELIPK F1EK Complete elliptic integral of the first kind; DELIPE F1EE Complete elliptic integral of the second kind; DEI F1EI Exponential integrals; NATSPSI F2PS Psi (logarithmic derivative of gamma function); MONERR F1MO Error monitoring package . 2 - Method of solution: FUNPACK uses evaluation of min-max approximations
Directory of Open Access Journals (Sweden)
Cristinel Mortici
2015-01-01
Full Text Available In this survey we present our recent results on analysis of gamma function and related functions. The results obtained are in the theory of asymptotic analysis, approximation of gamma and polygamma functions, or in the theory of completely monotonic functions. The motivation of this first part is the work of C. Mortici [Product Approximations via Asymptotic Integration Amer. Math. Monthly 117 (2010 434-441] where a simple strategy for constructing asymptotic series is presented. The classical asymptotic series associated to Stirling, Wallis, Glaisher-Kinkelin are rediscovered. In the second section we discuss some new inequalities related to Landau constants and we establish some asymptotic formulas.
International Nuclear Information System (INIS)
Haeggblom, H.
1968-08-01
The method of calculating the resonance interaction effect by series expansions has been studied. Starting from the assumption that the neutron flux in a homogeneous mixture is inversely proportional to the total cross section, the expression for the flux can be simplified by series expansions. Two types of expansions are investigated and it is shown that only one of them is generally applicable. It is also shown that this expansion gives sufficient accuracy if the approximate resonance line shape function is reasonably representative. An investigation is made of the approximation of the resonance shape function with a Gaussian function which in some cases has been used to calculate the interaction effect. It is shown that this approximation is not sufficiently accurate in all cases which can occur in practice. Then, a rational approximation is introduced which in the first order approximation gives the same order of accuracy as a practically exact shape function. The integrations can be made analytically in the complex plane and the method is therefore very fast compared to purely numerical integrations. The method can be applied both to statistically correlated and uncorrelated resonances
Energy Technology Data Exchange (ETDEWEB)
Haeggblom, H
1968-08-15
The method of calculating the resonance interaction effect by series expansions has been studied. Starting from the assumption that the neutron flux in a homogeneous mixture is inversely proportional to the total cross section, the expression for the flux can be simplified by series expansions. Two types of expansions are investigated and it is shown that only one of them is generally applicable. It is also shown that this expansion gives sufficient accuracy if the approximate resonance line shape function is reasonably representative. An investigation is made of the approximation of the resonance shape function with a Gaussian function which in some cases has been used to calculate the interaction effect. It is shown that this approximation is not sufficiently accurate in all cases which can occur in practice. Then, a rational approximation is introduced which in the first order approximation gives the same order of accuracy as a practically exact shape function. The integrations can be made analytically in the complex plane and the method is therefore very fast compared to purely numerical integrations. The method can be applied both to statistically correlated and uncorrelated resonances.
Bridge density functional approximation for non-uniform hard core repulsive Yukawa fluid
International Nuclear Information System (INIS)
Zhou Shiqi
2008-01-01
In this work, a bridge density functional approximation (BDFA) (J. Chem. Phys. 112, 8079 (2000)) for a non-uniform hard-sphere fluid is extended to a non-uniform hard-core repulsive Yukawa (HCRY) fluid. It is found that the choice of a bulk bridge functional approximation is crucial for both a uniform HCRY fluid and a non-uniform HCRY fluid. A new bridge functional approximation is proposed, which can accurately predict the radial distribution function of the bulk HCRY fluid. With the new bridge functional approximation and its associated bulk second order direct correlation function as input, the BDFA can be used to well calculate the density profile of the HCRY fluid subjected to the influence of varying external fields, and the theoretical predictions are in good agreement with the corresponding simulation data. The calculated results indicate that the present BDFA captures quantitatively the phenomena such as the coexistence of solid-like high density phase and low density gas phase, and the adsorption properties of the HCRY fluid, which qualitatively differ from those of the fluids combining both hard-core repulsion and an attractive tail. (condensed matter: structure, thermal and mechanical properties)
Balancing Exchange Mixing in Density-Functional Approximations for Iron Porphyrin.
Berryman, Victoria E J; Boyd, Russell J; Johnson, Erin R
2015-07-14
Predicting the correct ground-state multiplicity for iron(II) porphyrin, a high-spin quintet, remains a significant challenge for electronic-structure methods, including commonly employed density functionals. An even greater challenge for these methods is correctly predicting favorable binding of O2 to iron(II) porphyrin, due to the open-shell singlet character of the adduct. In this work, the performance of a modest set of contemporary density-functional approximations is assessed and the results interpreted using Bader delocalization indices. It is found that inclusion of greater proportions of Hartree-Fock exchange, in hybrid or range-separated hybrid functionals, has opposing effects; it improves the ability of the functional to identify the ground state but is detrimental to predicting favorable dioxygen binding. Because of the uncomplementary nature of these properties, accurate prediction of both the relative spin-state energies and the O2 binding enthalpy eludes conventional density-functional approximations.
Slow Growth and Optimal Approximation of Pseudoanalytic Functions on the Disk
Directory of Open Access Journals (Sweden)
Devendra Kumar
2013-07-01
Full Text Available Pseudoanalytic functions (PAF are constructed as complex combination of real-valued analytic solutions to the Stokes-Betrami System. These solutions include the generalized biaxisymmetric potentials. McCoy [10] considered the approximation of pseudoanalytic functions on the disk. Kumar et al. [9] studied the generalized order and generalized type of PAF in terms of the Fourier coefficients occurring in its local expansion and optimal approximation errors in Bernstein sense on the disk. The aim of this paper is to improve the results of McCoy [10] and Kumar et al. [9]. Our results apply satisfactorily for slow growth.
Zhou, Chenyi; Guo, Hong
2017-01-01
We report a diagrammatic method to solve the general problem of calculating configurationally averaged Green's function correlators that appear in quantum transport theory for nanostructures containing disorder. The theory treats both equilibrium and nonequilibrium quantum statistics on an equal footing. Since random impurity scattering is a problem that cannot be solved exactly in a perturbative approach, we combine our diagrammatic method with the coherent potential approximation (CPA) so that a reliable closed-form solution can be obtained. Our theory not only ensures the internal consistency of the diagrams derived at different levels of the correlators but also satisfies a set of Ward-like identities that corroborate the conserving consistency of transport calculations within the formalism. The theory is applied to calculate the quantum transport properties such as average ac conductance and transmission moments of a disordered tight-binding model, and results are numerically verified to high precision by comparing to the exact solutions obtained from enumerating all possible disorder configurations. Our formalism can be employed to predict transport properties of a wide variety of physical systems where disorder scattering is important.
Badillo-Olvera, A.; Begovich, O.; Peréz-González, A.
2017-01-01
The present paper is motivated by the purpose of detection and isolation of a single leak considering the Fault Model Approach (FMA) focused on pipelines with changes in their geometry. These changes generate a different pressure drop that those produced by the friction, this phenomenon is a common scenario in real pipeline systems. The problem arises, since the dynamical model of the fluid in a pipeline only considers straight geometries without fittings. In order to address this situation, several papers work with a virtual model of a pipeline that generates a equivalent straight length, thus, friction produced by the fittings is taking into account. However, when this method is applied, the leak is isolated in a virtual length, which for practical reasons does not represent a complete solution. This research proposes as a solution to the problem of leak isolation in a virtual length, the use of a polynomial interpolation function in order to approximate the conversion of the virtual position to a real-coordinates value. Experimental results in a real prototype are shown, concluding that the proposed methodology has a good performance.
Yang, Jingjing; Cox, Dennis D; Lee, Jong Soo; Ren, Peng; Choi, Taeryon
2017-12-01
Functional data are defined as realizations of random functions (mostly smooth functions) varying over a continuum, which are usually collected on discretized grids with measurement errors. In order to accurately smooth noisy functional observations and deal with the issue of high-dimensional observation grids, we propose a novel Bayesian method based on the Bayesian hierarchical model with a Gaussian-Wishart process prior and basis function representations. We first derive an induced model for the basis-function coefficients of the functional data, and then use this model to conduct posterior inference through Markov chain Monte Carlo methods. Compared to the standard Bayesian inference that suffers serious computational burden and instability in analyzing high-dimensional functional data, our method greatly improves the computational scalability and stability, while inheriting the advantage of simultaneously smoothing raw observations and estimating the mean-covariance functions in a nonparametric way. In addition, our method can naturally handle functional data observed on random or uncommon grids. Simulation and real studies demonstrate that our method produces similar results to those obtainable by the standard Bayesian inference with low-dimensional common grids, while efficiently smoothing and estimating functional data with random and high-dimensional observation grids when the standard Bayesian inference fails. In conclusion, our method can efficiently smooth and estimate high-dimensional functional data, providing one way to resolve the curse of dimensionality for Bayesian functional data analysis with Gaussian-Wishart processes. © 2017, The International Biometric Society.
DEFF Research Database (Denmark)
Opper, Manfred; Winther, Ole
2001-01-01
We develop an advanced mean held method for approximating averages in probabilistic data models that is based on the Thouless-Anderson-Palmer (TAP) approach of disorder physics. In contrast to conventional TAP. where the knowledge of the distribution of couplings between the random variables...... is required. our method adapts to the concrete couplings. We demonstrate the validity of our approach, which is so far restricted to models with nonglassy behavior? by replica calculations for a wide class of models as well as by simulations for a real data set....
A new formulation for the Doppler broadening function relaxing the approximations of Beth–Plackzec
International Nuclear Information System (INIS)
Palma, Daniel A.P.; Gonçalves, Alessandro C.; Martinez, Aquilino S.; Mesquita, Amir Z.
2016-01-01
Highlights: • One of the Beth–Placzek approximation were relaxed. • An additional term in the form of an integral is obtained. • A new mathematical formulation for the Doppler broadening function is proposed. - Abstract: In all nuclear reactors some neutrons can be absorbed in the resonance region and, in the design of these reactors, an accurate treatment of the resonant absorptions is essential. Apart from that, the resonant absorption varies with fuel temperature due to the Doppler broadening of the resonances. The thermal agitation movement in the reactor core is adequately represented in the microscopic cross-section of the neutron-core interaction through the Doppler broadening function. This function is calculated numerically in modern systems for the calculation of macro-group constants, necessary to determine the power distribution of a nuclear reactor. It can also be applied to the calculation of self-shielding factors to correct the measurements of the microscopic cross-sections through the activation technique and used for the approximate calculations of the resonance integrals in heterogeneous fuel cells. In these types of application we can point at the need to develop precise analytical approximations for the Doppler broadening function to be used in the calculation codes that calculate the values of this function. However, the Doppler broadening function is based on a series of approximations proposed by Beth–Plackzec. In this work a relaxation of these approximations is proposed, generating an additional term in the form of an integral. Analytical solutions of this additional term are discussed. The results obtained show that the new term is important for high temperatures.
International Nuclear Information System (INIS)
Lublinsky, Michael
2004-01-01
A simple analytic expression for the nonsinglet structure function f NS is given. The expression is derived from the result of Ermolaev, Manaenkov, and Ryskin obtained by low x resummation of the quark ladder diagrams in the double logarithmic approximation of perturbative QCD
APPROX, 1-D and 2-D Function Approximation by Polynomials, Splines, Finite Elements Method
International Nuclear Information System (INIS)
Tollander, Bengt
1975-01-01
1 - Nature of physical problem solved: Approximates one- and two- dimensional functions using different forms of the approximating function, as polynomials, rational functions, Splines and (or) the finite element method. Different kinds of transformations of the dependent and (or) the independent variables can easily be made by data cards using a FORTRAN-like language. 2 - Method of solution: Approximations by polynomials, Splines and (or) the finite element method are made in L2 norm using the least square method by which the answer is directly given. For rational functions in one dimension the result given in L(infinite) norm is achieved by iterations moving the zero points of the error curve. For rational functions in two dimensions, the norm is L2 and the result is achieved by iteratively changing the coefficients of the denominator and then solving the coefficients of the numerator by the least square method. The transformation of the dependent and (or) independent variables is made by compiling the given transform data card(s) to an array of integers from which the transformation can be made
Approximated calculation of the vacuum wave function and vacuum energy of the LGT with RPA method
International Nuclear Information System (INIS)
Hui Ping
2004-01-01
The coupled cluster method is improved with the random phase approximation (RPA) to calculate vacuum wave function and vacuum energy of 2 + 1 - D SU(2) lattice gauge theory. In this calculating, the trial wave function composes of single-hollow graphs. The calculated results of vacuum wave functions show very good scaling behaviors at weak coupling region l/g 2 >1.2 from the third order to the sixth order, and the vacuum energy obtained with RPA method is lower than the vacuum energy obtained without RPA method, which means that this method is a more efficient one
Zeng, Lang; He, Yu; Povolotskyi, Michael; Liu, XiaoYan; Klimeck, Gerhard; Kubis, Tillmann
2013-06-01
In this work, the low rank approximation concept is extended to the non-equilibrium Green's function (NEGF) method to achieve a very efficient approximated algorithm for coherent and incoherent electron transport. This new method is applied to inelastic transport in various semiconductor nanodevices. Detailed benchmarks with exact NEGF solutions show (1) a very good agreement between approximated and exact NEGF results, (2) a significant reduction of the required memory, and (3) a large reduction of the computational time (a factor of speed up as high as 150 times is observed). A non-recursive solution of the inelastic NEGF transport equations of a 1000 nm long resistor on standard hardware illustrates nicely the capability of this new method.
Deep-inelastic structure functions in an approximation to the bag theory
International Nuclear Information System (INIS)
Jaffe, R.L.
1975-01-01
A cavity approximation to the bag theory developed earlier is extended to the treatment of forward virtual Compton scattering. In the Bjorken limit and for small values of ω (ω = vertical-bar2p center-dot q/q 2 vertical-bar) it is argued that the operator nature of the bag boundaries might be ignored. Structure functions are calculated in one and three dimensions. Bjorken scaling is obtained. The model provides a realization of light-cone current algebra and possesses a parton interpretation. The structure functions show a quasielastic peak. The spreading of the structure functions about the peak is associated with confinement. As expected, Regge behavior is not obtained for large ω. The ''momentum sum rule'' is saturated, indicating that the hadron's charged constituents carry all the momentum in this model. νW/subL/ is found to scale and is calculable. Application of the model to the calculation of spin-dependent and chiral-symmetry--violating structure functions is proposed. The nature of the intermediate states in this approximation is discussed. Problems associated with the cavity approximation are also discussed
Two site spin correlation function in Bethe-Peierls approximation for Ising model
Energy Technology Data Exchange (ETDEWEB)
Kumar, D [Roorkee Univ. (India). Dept. of Physics
1976-07-01
Two site spin correlation function for an Ising model above Curie temperature has been calculated by generalising Bethe-Peierls approximation. The results derived by a graphical method due to Englert are essentially the same as those obtained earlier by Elliott and Marshall, and Oguchi and Ono. The earlier results were obtained by a direct generalisation of the cluster method of Bethe, while these results are derived by retaining that class of diagrams , which is exact on Bethe lattice.
International Nuclear Information System (INIS)
D’Amore, L; Campagna, R; Murli, A; Galletti, A; Marcellino, L
2012-01-01
The scientific and application-oriented interest in the Laplace transform and its inversion is testified by more than 1000 publications in the last century. Most of the inversion algorithms available in the literature assume that the Laplace transform function is available everywhere. Unfortunately, such an assumption is not fulfilled in the applications of the Laplace transform. Very often, one only has a finite set of data and one wants to recover an estimate of the inverse Laplace function from that. We propose a fitting model of data. More precisely, given a finite set of measurements on the real axis, arising from an unknown Laplace transform function, we construct a dth degree generalized polynomial smoothing spline, where d = 2m − 1, such that internally to the data interval it is a dth degree polynomial complete smoothing spline minimizing a regularization functional, and outside the data interval, it mimics the Laplace transform asymptotic behavior, i.e. it is a rational or an exponential function (the end behavior model), and at the boundaries of the data set it joins with regularity up to order m − 1, with the end behavior model. We analyze in detail the generalized polynomial smoothing spline of degree d = 3. This choice was motivated by the (ill)conditioning of the numerical computation which strongly depends on the degree of the complete spline. We prove existence and uniqueness of this spline. We derive the approximation error and give a priori and computable bounds of it on the whole real axis. In such a way, the generalized polynomial smoothing spline may be used in any real inversion algorithm to compute an approximation of the inverse Laplace function. Experimental results concerning Laplace transform approximation, numerical inversion of the generalized polynomial smoothing spline and comparisons with the exponential smoothing spline conclude the work. (paper)
Zeroth order regular approximation approach to electric dipole moment interactions of the electron
Gaul, Konstantin; Berger, Robert
2017-07-01
A quasi-relativistic two-component approach for an efficient calculation of P ,T -odd interactions caused by a permanent electric dipole moment of the electron (eEDM) is presented. The approach uses a (two-component) complex generalized Hartree-Fock and a complex generalized Kohn-Sham scheme within the zeroth order regular approximation. In applications to select heavy-elemental polar diatomic molecular radicals, which are promising candidates for an eEDM experiment, the method is compared to relativistic four-component electron-correlation calculations and confirms values for the effective electric field acting on the unpaired electron for RaF, BaF, YbF, and HgF. The calculations show that purely relativistic effects, involving only the lower component of the Dirac bi-spinor, are well described by treating only the upper component explicitly.
An approximate dynamic programming approach to resource management in multi-cloud scenarios
Pietrabissa, Antonio; Priscoli, Francesco Delli; Di Giorgio, Alessandro; Giuseppi, Alessandro; Panfili, Martina; Suraci, Vincenzo
2017-03-01
The programmability and the virtualisation of network resources are crucial to deploy scalable Information and Communications Technology (ICT) services. The increasing demand of cloud services, mainly devoted to the storage and computing, requires a new functional element, the Cloud Management Broker (CMB), aimed at managing multiple cloud resources to meet the customers' requirements and, simultaneously, to optimise their usage. This paper proposes a multi-cloud resource allocation algorithm that manages the resource requests with the aim of maximising the CMB revenue over time. The algorithm is based on Markov decision process modelling and relies on reinforcement learning techniques to find online an approximate solution.
Many-body perturbation theory using the density-functional concept: beyond the GW approximation
Bruneval, Fabien; Sottile, Francesco; Olevano, Valerio; Del Sole, Rodolfo; Reining, Lucia
2005-01-01
We propose an alternative formulation of Many-Body Perturbation Theory that uses the density-functional concept. Instead of the usual four-point integral equation for the polarizability, we obtain a two-point one, that leads to excellent optical absorption and energy loss spectra. The corresponding three-point vertex function and self-energy are then simply calculated via an integration, for any level of approximation. Moreover, we show the direct impact of this formulation on the time-depend...
International Nuclear Information System (INIS)
Lobanov, Yu.Yu.; Shidkov, E.P.
1987-01-01
The method for numerical evaluation of path integrals in Eucledean quantum mechanics without lattice discretization is elaborated. The method is based on the representation of these integrals in the form of functional integrals with respect to the conditional Wiener measure and on the use of the derived approximate exact on a class of polynomial functionals of a given degree. By the computations of non-perturbative characteristics, concerned the topological structure of vacuum, the advantages of this method versus lattice Monte-Carlo calculations are demonstrated
An intrinsic robust rank-one-approximation approach for currencyportfolio optimization
Directory of Open Access Journals (Sweden)
Hongxuan Huang
2018-03-01
Full Text Available A currency portfolio is a special kind of wealth whose value fluctuates with foreignexchange rates over time, which possesses 3Vs (volume, variety and velocity properties of big datain the currency market. In this paper, an intrinsic robust rank one approximation (ROA approachis proposed to maximize the value of currency portfolios over time. The main results of the paperinclude four parts: Firstly, under the assumptions about the currency market, the currency portfoliooptimization problem is formulated as the basic model, in which there are two types of variablesdescribing currency amounts in portfolios and the amount of each currency exchanged into another,respectively. Secondly, the rank one approximation problem and its variants are also formulated toapproximate a foreign exchange rate matrix, whose performance is measured by the Frobenius normor the 2-norm of a residual matrix. The intrinsic robustness of the rank one approximation is provedtogether with summarizing properties of the basic ROA problem and designing a modified powermethod to search for the virtual exchange rates hidden in a foreign exchange rate matrix. Thirdly,a technique for decision variables reduction is presented to attack the currency portfolio optimization.The reduced formulation is referred to as the ROA model, which keeps only variables describingcurrency amounts in portfolios. The optimal solution to the ROA model also induces a feasible solutionto the basic model of the currency portfolio problem by integrating forex operations from the ROAmodel with practical forex rates. Finally, numerical examples are presented to verify the feasibility ande ciency of the intrinsic robust rank one approximation approach. They also indicate that there existsan objective measure for evaluating and optimizing currency portfolios over time, which is related tothe virtual standard currency and independent of any real currency selected specially for measurement.
Exact solutions for fermionic Green's functions in the Bloch-Nordsieck approximation of QED
International Nuclear Information System (INIS)
Kernemann, A.; Stefanis, N.G.
1989-01-01
A set of new closed-form solutions for fermionic Green's functions in the Bloch-Nordsieck approximation of QED is presented. A manifestly covariant phase-space path-integral method is applied for calculating the n-fermion Green's function in a classical external field. In the case of one and two fermions, explicit expressions for the full Green's functions are analytically obtained, with renormalization carried out in the modified minimal subtraction scheme. The renormalization constants and the corresponding anomalous dimensions are determined. The mass-shell behavior of the two-fermion Green's function is investigated in detail. No assumptions are made concerning the structure of asymptotic states and no IR cutoff is used in the calculations
International Nuclear Information System (INIS)
Yonemitsu, K.; Bishop, A.R.
1992-01-01
As a convenient qualitative approach to strongly correlated electronic systems, an inhomogeneous Hartree-Fock plus random-phase approximation is applied to response functions for the two-dimensional multiband Hubbard model for cuprate superconductors. A comparison of the results with those obtained by exact diagonalization by Wagner, Hanke, and Scalapino [Phys. Rev. B 43, 10 517 (1991)] shows that overall structures in optical and magnetic particle-hole excitation spectra are well reproduced by this method. This approach is computationally simple, retains conceptual clarity, and can be calibrated by comparison with exact results on small systems. Most importantly, it is easily extended to larger systems and straightforward to incorporate additional terms in the Hamiltonian, such as electron-phonon interactions, which may play a crucial role in high-temperature superconductivity
Combi, Carlo; Mantovani, Matteo; Sabaini, Alberto; Sala, Pietro; Amaddeo, Francesco; Moretti, Ugo; Pozzi, Giuseppe
2015-07-01
Functional dependencies (FDs) typically represent associations over facts stored by a database, such as "patients with the same symptom get the same therapy." In more recent years, some extensions have been introduced to represent both temporal constraints (temporal functional dependencies - TFDs), as "for any given month, patients with the same symptom must have the same therapy, but their therapy may change from one month to the next one," and approximate properties (approximate functional dependencies - AFDs), as "patients with the same symptomgenerallyhave the same therapy." An AFD holds most of the facts stored by the database, enabling some data to deviate from the defined property: the percentage of data which violate the given property is user-defined. According to this scenario, in this paper we introduce approximate temporal functional dependencies (ATFDs) and use them to mine clinical data. Specifically, we considered the need for deriving new knowledge from psychiatric and pharmacovigilance data. ATFDs may be defined and measured either on temporal granules (e.g.grouping data by day, week, month, year) or on sliding windows (e.g.a fixed-length time interval which moves over the time axis): in this regard, we propose and discuss some specific and efficient data mining techniques for ATFDs. We also developed two running prototypes and showed the feasibility of our proposal by mining two real-world clinical data sets. The clinical interest of the dependencies derived considering the psychiatry and pharmacovigilance domains confirms the soundness and the usefulness of the proposed techniques. Copyright © 2014 Elsevier Ltd. All rights reserved.
Eikonal Approximation in AdS/CFT From Shock Waves to Four-Point Functions
Cornalba, L; Costa, Miguel S; Penedones, Joao; Cornalba, Lorenzo; Costa, M S; Penedones, J; Schiappa, Ricardo
2007-01-01
We initiate a program to generalize the standard eikonal approximation to compute amplitudes in Anti-de Sitter spacetimes. Inspired by the shock wave derivation of the eikonal amplitude in flat space, we study the two-point function E ~ _{shock} in the presence of a shock wave in Anti-de Sitter, where O_1 is a scalar primary operator in the dual conformal field theory. At tree level in the gravitational coupling, we relate the shock two-point function E to the discontinuity across a kinematical branch cut of the conformal field theory four-point function A ~ , where O_2 creates the shock geometry in Anti-de Sitter. Finally, we extend the above results by computing E in the presence of shock waves along the horizon of Schwarzschild BTZ black holes. This work gives new tools for the study of Planckian physics in Anti-de Sitter spacetimes.
Spherical Bessel transform via exponential sum approximation of spherical Bessel function
Ikeno, Hidekazu
2018-02-01
A new algorithm for numerical evaluation of spherical Bessel transform is proposed in this paper. In this method, the spherical Bessel function is approximately represented as an exponential sum with complex parameters. This is obtained by expressing an integral representation of spherical Bessel function in complex plane, and discretizing contour integrals along steepest descent paths and a contour path parallel to real axis using numerical quadrature rule with the double-exponential transformation. The number of terms in the expression is reduced using the modified balanced truncation method. The residual part of integrand is also expanded by exponential functions using Prony-like method. The spherical Bessel transform can be evaluated analytically on arbitrary points in half-open interval.
Efficient approximation of the incomplete gamma function for use in cloud model applications
Directory of Open Access Journals (Sweden)
U. Blahak
2010-07-01
Full Text Available This paper describes an approximation to the lower incomplete gamma function γ_{l}(a,x which has been obtained by nonlinear curve fitting. It comprises a fixed number of terms and yields moderate accuracy (the absolute approximation error of the corresponding normalized incomplete gamma function P is smaller than 0.02 in the range 0.9 ≤ a ≤ 45 and x≥0. Monotonicity and asymptotic behaviour of the original incomplete gamma function is preserved.
While providing a slight to moderate performance gain on scalar machines (depending on whether a stays the same for subsequent function evaluations or not compared to established and more accurate methods based on series- or continued fraction expansions with a variable number of terms, a big advantage over these more accurate methods is the applicability on vector CPUs. Here the fixed number of terms enables proper and efficient vectorization. The fixed number of terms might be also beneficial on massively parallel machines to avoid load imbalances, caused by a possibly vastly different number of terms in series expansions to reach convergence at different grid points. For many cloud microphysical applications, the provided moderate accuracy should be enough. However, on scalar machines and if a is the same for subsequent function evaluations, the most efficient method to evaluate incomplete gamma functions is perhaps interpolation of pre-computed regular lookup tables (most simple example: equidistant tables.
Xu, Zhenli; Ma, Manman; Liu, Pei
2014-07-01
We propose a modified Poisson-Nernst-Planck (PNP) model to investigate charge transport in electrolytes of inhomogeneous dielectric environment. The model includes the ionic polarization due to the dielectric inhomogeneity and the ion-ion correlation. This is achieved by the self energy of test ions through solving a generalized Debye-Hückel (DH) equation. We develop numerical methods for the system composed of the PNP and DH equations. Particularly, toward the numerical challenge of solving the high-dimensional DH equation, we developed an analytical WKB approximation and a numerical approach based on the selective inversion of sparse matrices. The model and numerical methods are validated by simulating the charge diffusion in electrolytes between two electrodes, for which effects of dielectrics and correlation are investigated by comparing the results with the prediction by the classical PNP theory. We find that, at the length scale of the interface separation comparable to the Bjerrum length, the results of the modified equations are significantly different from the classical PNP predictions mostly due to the dielectric effect. It is also shown that when the ion self energy is in weak or mediate strength, the WKB approximation presents a high accuracy, compared to precise finite-difference results.
Guliyev , Namig; Ismailov , Vugar
2016-01-01
The possibility of approximating a continuous function on a compact subset of the real line by a feedforward single hidden layer neural network with a sigmoidal activation function has been studied in many papers. Such networks can approximate an arbitrary continuous function provided that an unlimited number of neurons in a hidden layer is permitted. In this paper, we consider constructive approximation on any finite interval of $\\mathbb{R}$ by neural networks with only one neuron in the hid...
International Nuclear Information System (INIS)
Huh, Jae Sung; Kwak, Byung Man
2011-01-01
Robust optimization or reliability-based design optimization are some of the methodologies that are employed to take into account the uncertainties of a system at the design stage. For applying such methodologies to solve industrial problems, accurate and efficient methods for estimating statistical moments and failure probability are required, and further, the results of sensitivity analysis, which is needed for searching direction during the optimization process, should also be accurate. The aim of this study is to employ the function approximation moment method into the sensitivity analysis formulation, which is expressed as an integral form, to verify the accuracy of the sensitivity results, and to solve a typical problem of reliability-based design optimization. These results are compared with those of other moment methods, and the feasibility of the function approximation moment method is verified. The sensitivity analysis formula with integral form is the efficient formulation for evaluating sensitivity because any additional function calculation is not needed provided the failure probability or statistical moments are calculated
Mejia-Rodriguez, Daniel; Trickey, S. B.
2017-11-01
We explore the simplification of widely used meta-generalized-gradient approximation (mGGA) exchange-correlation functionals to the Laplacian level of refinement by use of approximate kinetic-energy density functionals (KEDFs). Such deorbitalization is motivated by the prospect of reducing computational cost while recovering a strictly Kohn-Sham local potential framework (rather than the usual generalized Kohn-Sham treatment of mGGAs). A KEDF that has been rather successful in solid simulations proves to be inadequate for deorbitalization, but we produce other forms which, with parametrization to Kohn-Sham results (not experimental data) on a small training set, yield rather good results on standard molecular test sets when used to deorbitalize the meta-GGA made very simple, Tao-Perdew-Staroverov-Scuseria, and strongly constrained and appropriately normed functionals. We also study the difference between high-fidelity and best-performing deorbitalizations and discuss possible implications for use in ab initio molecular dynamics simulations of complicated condensed phase systems.
Energy Technology Data Exchange (ETDEWEB)
Rudolph, E [Max-Planck-Institut fuer Physik und Astrophysik, Muenchen (F.R. Germany)
1975-01-01
As a model for gravitational radiation damping of a planet the electromagnetic radiation damping of an extended charged body moving in an external gravitational field is calculated in harmonic coordinates using a weak field, slowing-motion approximation. Special attention is paid to the case where this gravitational field is a weak Schwarzschild field. Using Green's function methods for this purpose it is shown that in a slow-motion approximation there is a strange connection between the tail part and the sharp part: radiation reaction terms of the tail part can cancel corresponding terms of the sharp part. Due to this cancelling mechanism the lowest order electromagnetic radiation damping force in an external gravitational field in harmonic coordinates remains the flat space Abraham Lorentz force. It is demonstrated in this simplified model that a naive slow-motion approximation may easily lead to divergent higher order terms. It is shown that this difficulty does not arise up to the considered order.
Heßelmann, Andreas
2015-04-14
Molecular excitation energies have been calculated with time-dependent density-functional theory (TDDFT) using random-phase approximation Hessians augmented with exact exchange contributions in various orders. It has been observed that this approach yields fairly accurate local valence excitations if combined with accurate asymptotically corrected exchange-correlation potentials used in the ground-state Kohn-Sham calculations. The inclusion of long-range particle-particle with hole-hole interactions in the kernel leads to errors of 0.14 eV only for the lowest excitations of a selection of three alkene, three carbonyl, and five azabenzene molecules, thus surpassing the accuracy of a number of common TDDFT and even some wave function correlation methods. In the case of long-range charge-transfer excitations, the method typically underestimates accurate reference excitation energies by 8% on average, which is better than with standard hybrid-GGA functionals but worse compared to range-separated functional approximations.
Fall with linear drag and Wien's displacement law: approximate solution and Lambert function
International Nuclear Information System (INIS)
Vial, Alexandre
2012-01-01
We present an approximate solution for the downward time of travel in the case of a mass falling with a linear drag force. We show how a quasi-analytical solution implying the Lambert function can be found. We also show that solving the previous problem is equivalent to the search for Wien's displacement law. These results can be of interest for undergraduate students, as they show that some transcendental equations found in physics may be solved without purely numerical methods. Moreover, as will be seen in the case of Wien's displacement law, solutions based on series expansion can be very accurate even with few terms. (paper)
A Method of Approximating Expectations of Functions of Sums of Independent Random Variables
Klass, Michael J.
1981-01-01
Let $X_1, X_2, \\cdots$ be a sequence of independent random variables with $S_n = \\sum^n_{i = 1} X_i$. Fix $\\alpha > 0$. Let $\\Phi(\\cdot)$ be a continuous, strictly increasing function on $\\lbrack 0, \\infty)$ such that $\\Phi(0) = 0$ and $\\Phi(cx) \\leq c^\\alpha\\Phi(x)$ for all $x > 0$ and all $c \\geq 2$. Suppose $a$ is a real number and $J$ is a finite nonempty subset of the positive integers. In this paper we are interested in approximating $E \\max_{j \\in J} \\Phi(|a + S_j|)$. We construct a nu...
Approximate Stream Function wavemaker theory for highly non-linear waves in wave flumes
DEFF Research Database (Denmark)
Zhang, H.W.; Schäffer, Hemming Andreas
2007-01-01
An approximate Stream Function wavemaker theory for highly non-linear regular waves in flumes is presented. This theory is based on an ad hoe unified wave-generation method that combines linear fully dispersive wavemaker theory and wave generation for non-linear shallow water waves. This is done...... by applying a dispersion correction to the paddle position obtained for non-linear long waves. The method is validated by a number of wave flume experiments while comparing with results of linear wavemaker theory, second-order wavemaker theory and Cnoidal wavemaker theory within its range of application....
Garza, Alejandro J.
Perhaps the most important approximations to the electronic structure problem in quantum chemistry are those based on coupled cluster and density functional theories. Coupled cluster theory has been called the ``gold standard'' of quantum chemistry due to the high accuracy that it achieves for weakly correlated systems. Kohn-Sham density functionals based on semilocal approximations are, without a doubt, the most widely used methods in chemistry and material science because of their high accuracy/cost ratio. The root of the success of coupled cluster and density functionals is their ability to efficiently describe the dynamic part of the electron correlation. However, both traditional coupled cluster and density functional approximations may fail catastrophically when substantial static correlation is present. This severely limits the applicability of these methods to a plethora of important chemical and physical problems such as, e.g., the description of bond breaking, transition states, transition metal-, lanthanide- and actinide-containing compounds, and superconductivity. In an attempt to tackle this problem, nonstandard (single-reference) coupled cluster-based techniques that aim to describe static correlation have been recently developed: pair coupled cluster doubles (pCCD) and singlet-paired coupled cluster doubles (CCD0). The ability to describe static correlation in pCCD and CCD0 comes, however, at the expense of important amounts of dynamic correlation so that the high accuracy of standard coupled cluster becomes unattainable. Thus, the reliable and efficient description of static and dynamic correlation in a simultaneous manner remains an open problem for quantum chemistry and many-body theory in general. In this thesis, different ways to combine pCCD and CCD0 with density functionals in order to describe static and dynamic correlation simultaneously (and efficiently) are explored. The combination of wavefunction and density functional methods has a long
Impaired neural networks for approximate calculation in dyscalculic children: a functional MRI study
Directory of Open Access Journals (Sweden)
Dosch Mengia
2006-09-01
Full Text Available Abstract Background Developmental dyscalculia (DD is a specific learning disability affecting the acquisition of mathematical skills in children with otherwise normal general intelligence. The goal of the present study was to examine cerebral mechanisms underlying DD. Methods Eighteen children with DD aged 11.2 ± 1.3 years and twenty age-matched typically achieving schoolchildren were investigated using functional magnetic resonance imaging (fMRI during trials testing approximate and exact mathematical calculation, as well as magnitude comparison. Results Children with DD showed greater inter-individual variability and had weaker activation in almost the entire neuronal network for approximate calculation including the intraparietal sulcus, and the middle and inferior frontal gyrus of both hemispheres. In particular, the left intraparietal sulcus, the left inferior frontal gyrus and the right middle frontal gyrus seem to play crucial roles in correct approximate calculation, since brain activation correlated with accuracy rate in these regions. In contrast, no differences between groups could be found for exact calculation and magnitude comparison. In general, fMRI revealed similar parietal and prefrontal activation patterns in DD children compared to controls for all conditions. Conclusion In conclusion, there is evidence for a deficient recruitment of neural resources in children with DD when processing analog magnitudes of numbers.
Ordered cones and approximation
Keimel, Klaus
1992-01-01
This book presents a unified approach to Korovkin-type approximation theorems. It includes classical material on the approximation of real-valuedfunctions as well as recent and new results on set-valued functions and stochastic processes, and on weighted approximation. The results are notonly of qualitative nature, but include quantitative bounds on the order of approximation. The book is addressed to researchers in functional analysis and approximation theory as well as to those that want to applythese methods in other fields. It is largely self- contained, but the readershould have a solid background in abstract functional analysis. The unified approach is based on a new notion of locally convex ordered cones that are not embeddable in vector spaces but allow Hahn-Banach type separation and extension theorems. This concept seems to be of independent interest.
Fast generation of macro basis functions for LEGO through the adaptive cross approximation
Lancellotti, V.
2015-01-01
We present a method for the fast generation of macro basis functions in the context of the linear embedding via Green's operators approach (LEGO) which is a domain decomposition technique based on the combination of electromagnetic bricks in turn described by means of scattering operators. We show
Hinuma, Yoyo; Hayashi, Hiroyuki; Kumagai, Yu; Tanaka, Isao; Oba, Fumiyasu
2017-09-01
High-throughput first-principles calculations based on density functional theory (DFT) are a powerful tool in data-oriented materials research. The choice of approximation to the exchange-correlation functional is crucial as it strongly affects the accuracy of DFT calculations. This study compares performance of seven approximations, six of which are based on Perdew-Burke-Ernzerhof (PBE) generalized gradient approximation (GGA) with and without Hubbard U and van der Waals corrections (PBE, PBE+U, PBED3, PBED3+U, PBEsol, and PBEsol+U), and the strongly constrained and appropriately normed (SCAN) meta-GGA on the energetics and crystal structure of elementary substances and binary oxides. For the latter, only those with closed-shell electronic structures are considered, examples of which include C u2O , A g2O , MgO, ZnO, CdO, SnO, PbO, A l2O3 , G a2O3 , I n2O3 , L a2O3 , B i2O3 , Si O2 , Sn O2 , Pb O2 , Ti O2 , Zr O2 , Hf O2 , V2O5 , N b2O5 , T a2O5 , Mo O3 , and W O3 . Prototype crystal structures are selected from the Inorganic Crystal Structure Database (ICSD) and cation substitution is used to make a set of existing and hypothetical oxides. Two indices are proposed to quantify the extent of lattice and internal coordinate relaxation during a calculation. The former is based on the second invariant and determinant of the transformation matrix of basis vectors from before relaxation to after relaxation, and the latter is derived from shifts of internal coordinates of atoms in the unit cell. PBED3, PBEsol, and SCAN reproduce experimental lattice parameters of elementary substances and oxides well with few outliers. Notably, PBEsol and SCAN predict the lattice parameters of low dimensional structures comparably well with PBED3, even though these two functionals do not explicitly treat van der Waals interactions. SCAN gives formation enthalpies and Gibbs free energies closest to experimental data, with mean errors (MEs) of 0.01 and -0.04 eV, respectively, and root
Székely, Balázs; Kania, Adam; Varga, Katalin; Heilmeier, Hermann
2017-04-01
Lacunarity, a measure of the spatial distribution of the empty space is found to be a useful descriptive quantity of the forest structure. Its calculation, based on laser-scanned point clouds, results in a four-dimensional data set. The evaluation of results needs sophisticated tools and visualization techniques. To simplify the evaluation, it is straightforward to use approximation functions fitted to the results. The lacunarity function L(r), being a measure of scale-independent structural properties, has a power-law character. Previous studies showed that log(log(L(r))) transformation is suitable for analysis of spatial patterns. Accordingly, transformed lacunarity functions can be approximated by appropriate functions either in the original or in the transformed domain. As input data we have used a number of laser-scanned point clouds of various forests. The lacunarity distribution has been calculated along a regular horizontal grid at various (relative) elevations. The lacunarity data cube then has been logarithm-transformed and the resulting values became the input of parameter estimation at each point (point of interest, POI). This way at each POI a parameter set is generated that is suitable for spatial analysis. The expectation is that the horizontal variation and vertical layering of the vegetation can be characterized by this procedure. The results show that the transformed L(r) functions can be typically approximated by exponentials individually, and the residual values remain low in most cases. However, (1) in most cases the residuals may vary considerably, and (2) neighbouring POIs often give rather differing estimates both in horizontal and in vertical directions, of them the vertical variation seems to be more characteristic. In the vertical sense, the distribution of estimates shows abrupt changes at places, presumably related to the vertical structure of the forest. In low relief areas horizontal similarity is more typical, in higher relief areas
Aft-body loading function for penetrators based on the spherical cavity-expansion approximation.
Energy Technology Data Exchange (ETDEWEB)
Longcope, Donald B., Jr.; Warren, Thomas Lynn; Duong, Henry
2009-12-01
In this paper we develop an aft-body loading function for penetration simulations that is based on the spherical cavity-expansion approximation. This loading function assumes that there is a preexisting cavity of radius a{sub o} before the expansion occurs. This causes the radial stress on the cavity surface to be less than what is obtained if the cavity is opened from a zero initial radius. This in turn causes less resistance on the aft body as it penetrates the target which allows for greater rotation of the penetrator. Results from simulations are compared with experimental results for oblique penetration into a concrete target with an unconfined compressive strength of 23 MPa.
Random phase approximations for the screening function in high Tc superconductors
International Nuclear Information System (INIS)
Lopez-Aguilar, F.; Costa-Quintana, J.; Sanchez, A.; Puig, T.; Aurell, M.T.; Martinez, L.M.; Munoz, J.S.
1990-01-01
This paper reports on the electronic transferences from the CuO 2 sheets toward the CuO 3 linear chain, which locate electrons in the orbitals p y /p z of O4/O1 and d z 2 -y 2 of Cu1, and holes in the orbitals d x 2 -y 2 - P z /p y of Cu2 - P2/O3. These holes states present large interatomic overlapping. In this paper, we determine the screening function within the random phase approximation applied to the high-T c superconductors. This screening function is vanishing for determined values of the frequency which correspond to renormalized plasmon frequencies. These frequencies depends on the band parameters and their knowledge is essential for determining the self energy. This self energy is deduced and it contain independent terms for each of the channels for the localization
Analytic number theory, approximation theory, and special functions in honor of Hari M. Srivastava
Rassias, Michael
2014-01-01
This book, in honor of Hari M. Srivastava, discusses essential developments in mathematical research in a variety of problems. It contains thirty-five articles, written by eminent scientists from the international mathematical community, including both research and survey works. Subjects covered include analytic number theory, combinatorics, special sequences of numbers and polynomials, analytic inequalities and applications, approximation of functions and quadratures, orthogonality, and special and complex functions. The mathematical results and open problems discussed in this book are presented in a simple and self-contained manner. The book contains an overview of old and new results, methods, and theories toward the solution of longstanding problems in a wide scientific field, as well as new results in rapidly progressing areas of research. The book will be useful for researchers and graduate students in the fields of mathematics, physics, and other computational and applied sciences.
Single image super-resolution based on approximated Heaviside functions and iterative refinement
Wang, Xin-Yu; Huang, Ting-Zhu; Deng, Liang-Jian
2018-01-01
One method of solving the single-image super-resolution problem is to use Heaviside functions. This has been done previously by making a binary classification of image components as “smooth” and “non-smooth”, describing these with approximated Heaviside functions (AHFs), and iteration including l1 regularization. We now introduce a new method in which the binary classification of image components is extended to different degrees of smoothness and non-smoothness, these components being represented by various classes of AHFs. Taking into account the sparsity of the non-smooth components, their coefficients are l1 regularized. In addition, to pick up more image details, the new method uses an iterative refinement for the residuals between the original low-resolution input and the downsampled resulting image. Experimental results showed that the new method is superior to the original AHF method and to four other published methods. PMID:29329298
Lee, K. David; Wiesenfeld, Eric; Gelfand, Andrew
2007-04-01
One of the greatest challenges in modern combat is maintaining a high level of timely Situational Awareness (SA). In many situations, computational complexity and accuracy considerations make the development and deployment of real-time, high-level inference tools very difficult. An innovative hybrid framework that combines Bayesian inference, in the form of Bayesian Networks, and Possibility Theory, in the form of Fuzzy Logic systems, has recently been introduced to provide a rigorous framework for high-level inference. In previous research, the theoretical basis and benefits of the hybrid approach have been developed. However, lacking is a concrete experimental comparison of the hybrid framework with traditional fusion methods, to demonstrate and quantify this benefit. The goal of this research, therefore, is to provide a statistical analysis on the comparison of the accuracy and performance of hybrid network theory, with pure Bayesian and Fuzzy systems and an inexact Bayesian system approximated using Particle Filtering. To accomplish this task, domain specific models will be developed under these different theoretical approaches and then evaluated, via Monte Carlo Simulation, in comparison to situational ground truth to measure accuracy and fidelity. Following this, a rigorous statistical analysis of the performance results will be performed, to quantify the benefit of hybrid inference to other fusion tools.
International Nuclear Information System (INIS)
Gougam, L.A.; Taibi, H.; Chikhi, A.; Mekideche-Chafa, F.
2009-01-01
The problem of determining the analytical description for a set of data arises in numerous sciences and applications and can be referred to as data modeling or system identification. Neural networks are a convenient means of representation because they are known to be universal approximates that can learn data. The desired task is usually obtained by a learning procedure which consists in adjusting the s ynaptic weights . For this purpose, many learning algorithms have been proposed to update these weights. The convergence for these learning algorithms is a crucial criterion for neural networks to be useful in different applications. The aim of the present contribution is to use a training algorithm for feed forward wavelet networks used for function approximation. The training is based on the minimization of the least-square cost function. The minimization is performed by iterative second order gradient-based methods. We make use of the Levenberg-Marquardt algorithm to train the architecture of the chosen network and, then, the training procedure starts with a simple gradient method which is followed by a BFGS (Broyden, Fletcher, Glodfarb et Shanno) algorithm. The performances of the two algorithms are then compared. Our method is then applied to determine the energy of the ground state associated to a sextic potential. In fact, the Schrodinger equation does not always admit an exact solution and one has, generally, to solve it numerically. To this end, the sextic potential is, firstly, approximated with the above outlined wavelet network and, secondly, implemented into a numerical scheme. Our results are in good agreement with the ones found in the literature.
International Nuclear Information System (INIS)
Al-Hawat, Sh; Naddaf, M
2005-01-01
The electron energy distribution function (EEDF) was determined from the second derivative of the I-V Langmuir probe characteristics and, thereafter, theoretically calculated by solving the plasma kinetic equation, using the black wall (BW) approximation, in the positive column of a neon glow discharge. The pressure has been varied from 0.5 to 4 Torr and the current from 10 to 30 mA. The measured electron temperature, density and electric field strength were used as input data for solving the kinetic equation. Comparisons were made between the EEDFs obtained from experiment, the BW approach, the Maxwellian distribution and the Rutcher solution of the kinetic equation in the elastic energy range. The best conditions for the BW approach are found to be under the discharge conditions: current density j d = 4.45 mA cm -2 and normalized electric field strength E/p = 1.88 V cm -1 Torr -1
Al-Hawat, Sh; Naddaf, M.
2005-04-01
The electron energy distribution function (EEDF) was determined from the second derivative of the I-V Langmuir probe characteristics and, thereafter, theoretically calculated by solving the plasma kinetic equation, using the black wall (BW) approximation, in the positive column of a neon glow discharge. The pressure has been varied from 0.5 to 4 Torr and the current from 10 to 30 mA. The measured electron temperature, density and electric field strength were used as input data for solving the kinetic equation. Comparisons were made between the EEDFs obtained from experiment, the BW approach, the Maxwellian distribution and the Rutcher solution of the kinetic equation in the elastic energy range. The best conditions for the BW approach are found to be under the discharge conditions: current density jd = 4.45 mA cm-2 and normalized electric field strength E/p = 1.88 V cm-1 Torr-1.
Energy Technology Data Exchange (ETDEWEB)
Jennings, Elise; Wolf, Rachel; Sako, Masao
2016-11-09
Cosmological parameter estimation techniques that robustly account for systematic measurement uncertainties will be crucial for the next generation of cosmological surveys. We present a new analysis method, superABC, for obtaining cosmological constraints from Type Ia supernova (SN Ia) light curves using Approximate Bayesian Computation (ABC) without any likelihood assumptions. The ABC method works by using a forward model simulation of the data where systematic uncertainties can be simulated and marginalized over. A key feature of the method presented here is the use of two distinct metrics, the `Tripp' and `Light Curve' metrics, which allow us to compare the simulated data to the observed data set. The Tripp metric takes as input the parameters of models fit to each light curve with the SALT-II method, whereas the Light Curve metric uses the measured fluxes directly without model fitting. We apply the superABC sampler to a simulated data set of $\\sim$1000 SNe corresponding to the first season of the Dark Energy Survey Supernova Program. Varying $\\Omega_m, w_0, \\alpha$ and $\\beta$ and a magnitude offset parameter, with no systematics we obtain $\\Delta(w_0) = w_0^{\\rm true} - w_0^{\\rm best \\, fit} = -0.036\\pm0.109$ (a $\\sim11$% 1$\\sigma$ uncertainty) using the Tripp metric and $\\Delta(w_0) = -0.055\\pm0.068$ (a $\\sim7$% 1$\\sigma$ uncertainty) using the Light Curve metric. Including 1% calibration uncertainties in four passbands, adding 4 more parameters, we obtain $\\Delta(w_0) = -0.062\\pm0.132$ (a $\\sim14$% 1$\\sigma$ uncertainty) using the Tripp metric. Overall we find a $17$% increase in the uncertainty on $w_0$ with systematics compared to without. We contrast this with a MCMC approach where systematic effects are approximately included. We find that the MCMC method slightly underestimates the impact of calibration uncertainties for this simulated data set.
Peck, Charles C.; Dhawan, Atam P.; Meyer, Claudia M.
1991-01-01
A genetic algorithm is used to select the inputs to a neural network function approximator. In the application considered, modeling critical parameters of the space shuttle main engine (SSME), the functional relationship between measured parameters is unknown and complex. Furthermore, the number of possible input parameters is quite large. Many approaches have been used for input selection, but they are either subjective or do not consider the complex multivariate relationships between parameters. Due to the optimization and space searching capabilities of genetic algorithms they were employed to systematize the input selection process. The results suggest that the genetic algorithm can generate parameter lists of high quality without the explicit use of problem domain knowledge. Suggestions for improving the performance of the input selection process are also provided.
International Nuclear Information System (INIS)
Klüser, Lars; Di Biagio, Claudia; Kleiber, Paul D.; Formenti, Paola; Grassian, Vicki H.
2016-01-01
Optical properties (extinction efficiency, single scattering albedo, asymmetry parameter and scattering phase function) of five different desert dust minerals have been calculated with an asymptotic approximation approach (AAA) for non-spherical particles. The AAA method combines Rayleigh-limit approximations with an asymptotic geometric optics solution in a simple and straightforward formulation. The simulated extinction spectra have been compared with classical Lorenz–Mie calculations as well as with laboratory measurements of dust extinction. This comparison has been done for single minerals and with bulk dust samples collected from desert environments. It is shown that the non-spherical asymptotic approximation improves the spectral extinction pattern, including position of the extinction peaks, compared to the Lorenz–Mie calculations for spherical particles. Squared correlation coefficients from the asymptotic approach range from 0.84 to 0.96 for the mineral components whereas the corresponding numbers for Lorenz–Mie simulations range from 0.54 to 0.85. Moreover the blue shift typically found in Lorenz–Mie results is not present in the AAA simulations. The comparison of spectra simulated with the AAA for different shape assumptions suggests that the differences mainly stem from the assumption of the particle shape and not from the formulation of the method itself. It has been shown that the choice of particle shape strongly impacts the quality of the simulations. Additionally, the comparison of simulated extinction spectra with bulk dust measurements indicates that within airborne dust the composition may be inhomogeneous over the range of dust particle sizes, making the calculation of reliable radiative properties of desert dust even more complex. - Highlights: • A fast and simple method for estimating optical properties of dust. • Can be used with non-spherical particles of arbitrary size distributions. • Comparison with Mie simulations and
Xia, Ya-Rong; Zhang, Shun-Li; Xin, Xiang-Peng
2018-03-01
In this paper, we propose the concept of the perturbed invariant subspaces (PISs), and study the approximate generalized functional variable separation solution for the nonlinear diffusion-convection equation with weak source by the approximate generalized conditional symmetries (AGCSs) related to the PISs. Complete classification of the perturbed equations which admit the approximate generalized functional separable solutions (AGFSSs) is obtained. As a consequence, some AGFSSs to the resulting equations are explicitly constructed by way of examples.
International Nuclear Information System (INIS)
Mery, P.
1977-01-01
The operator and matrix Pade approximation are defined. The fact that these approximants can be derived from the Schwinger variational principle is emphasized. In potential theory, using this variational aspect it is shown that the matrix Pade approximation allow to reproduce the exact solution of the Lippman-Schwinger equation with any required accuracy taking only into account the knowledge of the first two coefficients in the Born expansion. The deep analytic structure of this variational matrix Pade approximation (hyper Pade approximation) is discussed
Ito, Kazufumi; Teglas, Russell
1987-01-01
The numerical scheme based on the Legendre-tau approximation is proposed to approximate the feedback solution to the linear quadratic optimal control problem for hereditary differential systems. The convergence property is established using Trotter ideas. The method yields very good approximations at low orders and provides an approximation technique for computing closed-loop eigenvalues of the feedback system. A comparison with existing methods (based on averaging and spline approximations) is made.
Ito, K.; Teglas, R.
1984-01-01
The numerical scheme based on the Legendre-tau approximation is proposed to approximate the feedback solution to the linear quadratic optimal control problem for hereditary differential systems. The convergence property is established using Trotter ideas. The method yields very good approximations at low orders and provides an approximation technique for computing closed-loop eigenvalues of the feedback system. A comparison with existing methods (based on averaging and spline approximations) is made.
A novel approach for choosing summary statistics in approximate Bayesian computation.
Aeschbacher, Simon; Beaumont, Mark A; Futschik, Andreas
2012-11-01
The choice of summary statistics is a crucial step in approximate Bayesian computation (ABC). Since statistics are often not sufficient, this choice involves a trade-off between loss of information and reduction of dimensionality. The latter may increase the efficiency of ABC. Here, we propose an approach for choosing summary statistics based on boosting, a technique from the machine-learning literature. We consider different types of boosting and compare them to partial least-squares regression as an alternative. To mitigate the lack of sufficiency, we also propose an approach for choosing summary statistics locally, in the putative neighborhood of the true parameter value. We study a demographic model motivated by the reintroduction of Alpine ibex (Capra ibex) into the Swiss Alps. The parameters of interest are the mean and standard deviation across microsatellites of the scaled ancestral mutation rate (θ(anc) = 4N(e)u) and the proportion of males obtaining access to matings per breeding season (ω). By simulation, we assess the properties of the posterior distribution obtained with the various methods. According to our criteria, ABC with summary statistics chosen locally via boosting with the L(2)-loss performs best. Applying that method to the ibex data, we estimate θ(anc)≈ 1.288 and find that most of the variation across loci of the ancestral mutation rate u is between 7.7 × 10(-4) and 3.5 × 10(-3) per locus per generation. The proportion of males with access to matings is estimated as ω≈ 0.21, which is in good agreement with recent independent estimates.
On function classes related pertaining to strong approximation of double Fourier series
Baituyakova, Zhuldyz
2015-09-01
The investigation of embedding of function classes began a long time ago. After Alexits [1], Leindler [2], and Gogoladze[3] investigated estimates of strong approximation by Fourier series in 1965, G. Freud[4] raised the corresponding saturation problem in 1969. The list of the authors dealing with embedding problems partly is also very long. It suffices to mention some names: V. G. Krotov, W. Lenski, S. M. Mazhar, J. Nemeth, E. M. Nikisin, K. I. Oskolkov, G. Sunouchi, J. Szabados, R. Taberski and V. Totik. Study on this topic has since been carried on over a decade, but it seems that most of the results obtained are limited to the case of one dimension. In this paper, embedding results are considered which arise in the strong approximation by double Fourier series. We prove theorem on the interrelation between the classes Wr1,r2HS,M ω and H(λ, p, r1, r2, ω(δ1, δ2)), in the one-dimensional case proved by L. Leindler.
International Nuclear Information System (INIS)
Askar, S.S.; Alnowibet, K.
2016-01-01
Isoelastic demand function have been used in literature to study the dynamic features of systems constructed based on economic market structure. In this paper, we adopt the so-called Cobb–Douglas production function and study its impact on the steady state of an oligopolistic game that consists of four oligopolistic competitors or firms. Briefly, the paper handles three different scenarios. The first scenario introduces four oligopolistic firms who plays rational against each other in market. The firms use the myopic mechanism (or bounded rational) to update their production in the next time unit. The steady state of the obtained system in this scenario, which is the Nash equilibrium, is unique and its characteristics are investigated. Based on a local monopolistic approximation (LMA) strategy, one competitor prefers to play against the three rational firms and this is illustrated in the second scenario. The last scenario discusses the case when three competitors use the LMA strategy against a rational one. For all scenarios discrete dynamical systems are used to describe the game introduced in all scenarios. The stability analysis of the Nash equilibrium is investigated analytically and some numerical simulations are used to confirm the obtained analytical results.
A conceptual approach to approximate tree root architecture in infinite slope models
Schmaltz, Elmar; Glade, Thomas
2016-04-01
Vegetation-related properties - particularly tree root distribution and coherent hydrologic and mechanical effects on the underlying soil mantle - are commonly not considered in infinite slope models. Indeed, from a geotechnical point of view, these effects appear to be difficult to be reproduced reliably in a physically-based modelling approach. The growth of a tree and the expansion of its root architecture are directly connected with both intrinsic properties such as species and age, and extrinsic factors like topography, availability of nutrients, climate and soil type. These parameters control four main issues of the tree root architecture: 1) Type of rooting; 2) maximum growing distance to the tree stem (radius r); 3) maximum growing depth (height h); and 4) potential deformation of the root system. Geometric solids are able to approximate the distribution of a tree root system. The objective of this paper is to investigate whether it is possible to implement root systems and the connected hydrological and mechanical attributes sufficiently in a 3-dimensional slope stability model. Hereby, a spatio-dynamic vegetation module should cope with the demands of performance, computation time and significance. However, in this presentation, we focus only on the distribution of roots. The assumption is that the horizontal root distribution around a tree stem on a 2-dimensional plane can be described by a circle with the stem located at the centroid and a distinct radius r that is dependent on age and species. We classified three main types of tree root systems and reproduced the species-age-related root distribution with three respective mathematical solids in a synthetic 3-dimensional hillslope ambience. Thus, two solids in an Euclidian space were distinguished to represent the three root systems: i) cylinders with radius r and height h, whilst the dimension of latter defines the shape of a taproot-system or a shallow-root-system respectively; ii) elliptic
Approximate Receding Horizon Approach for Markov Decision Processes: Average Award Case
National Research Council Canada - National Science Library
Chang, Hyeong S; Marcus, Steven I
2002-01-01
...) with countable state space, finite action space, and bounded rewards that uses an approximate solution of a fixed finite-horizon sub-MDP of a given infinite-horizon MDP to create a stationary policy...
DEFF Research Database (Denmark)
Popov, Vladislav; Lavrinenko, Andrei; Novitsky, Andrey
2016-01-01
that the zeroth-, first-, and second-order approximations of the operator effective medium theory correspond to electric dipoles, chirality, and magnetic dipoles plus electric quadrupoles, respectively. We discover that the spatially dispersive bianisotropic effective medium obtained in the second...
Nakayama, Hiromasa
2006-01-01
We give an algorithm to compute the local $b$ function. In this algorithm, we use the Mora division algorithm in the ring of differential operators and an approximate division algorithm in the ring of differential operators with power series coefficient.
Bulk and interface dielectric functions: New results within the tight-binding approximation
International Nuclear Information System (INIS)
Elvira, V.D.; Duran, J.C.
1991-01-01
A tight-binding approach is used to analyze the dielectric behaviour of bulk semiconductors and semiconductor interfaces. This time interactions between second nearest neighbours are taken into account and several electrostatic models are proposed for the induced charge density around the atoms. The bulk dielectric function of different semiconductors (Si, Ge, GaAs and AlAs) are obtained and compared with other theoretical and experimental results. Finally, the energy band offset for GaAs-AlAs(1,0,0) interface is obtained and related to bulk properties of both semiconductors. The results presented in this paper show how the use of very simple but more realistic electrostatic models improve the analysis of the screening properties in semiconductors, giving a new support to the consistent tight-binding method for studying characteristics related to those properties. (Author)
International Nuclear Information System (INIS)
Basak, K C; Ray, P C; Bera, R K
2009-01-01
The aim of the present analysis is to apply the Adomian decomposition method and He's variational method for the approximate analytical solution of a nonlinear ordinary fractional differential equation. The solutions obtained by the above two methods have been numerically evaluated and presented in the form of tables and also compared with the exact solution. It was found that the results obtained by the above two methods are in excellent agreement with the exact solution. Finally, a surface plot of the approximate solutions of the fractional differential equation by the above two methods is drawn for 0≤t≤2 and 1<α≤2.
International Nuclear Information System (INIS)
Dalmasse, Kevin; Nychka, Douglas W.; Gibson, Sarah E.; Fan, Yuhong; Flyer, Natasha
2016-01-01
The Coronal Multichannel Polarimeter (CoMP) routinely performs coronal polarimetric measurements using the Fe XIII 10747 and 10798 lines, which are sensitive to the coronal magnetic field. However, inverting such polarimetric measurements into magnetic field data is a difficult task because the corona is optically thin at these wavelengths and the observed signal is therefore the integrated emission of all the plasma along the line of sight. To overcome this difficulty, we take on a new approach that combines a parameterized 3D magnetic field model with forward modeling of the polarization signal. For that purpose, we develop a new, fast and efficient, optimization method for model-data fitting: the Radial-basis-functions Optimization Approximation Method (ROAM). Model-data fitting is achieved by optimizing a user-specified log-likelihood function that quantifies the differences between the observed polarization signal and its synthetic/predicted analog. Speed and efficiency are obtained by combining sparse evaluation of the magnetic model with radial-basis-function (RBF) decomposition of the log-likelihood function. The RBF decomposition provides an analytical expression for the log-likelihood function that is used to inexpensively estimate the set of parameter values optimizing it. We test and validate ROAM on a synthetic test bed of a coronal magnetic flux rope and show that it performs well with a significantly sparse sample of the parameter space. We conclude that our optimization method is well-suited for fast and efficient model-data fitting and can be exploited for converting coronal polarimetric measurements, such as the ones provided by CoMP, into coronal magnetic field data.
A Volterra series approach to the approximation of stochastic nonlinear dynamics
Wouw, van de N.; Nijmeijer, H.; Campen, van D.H.
2002-01-01
A response approximation method for stochastically excited, nonlinear, dynamic systems is presented. Herein, the output of the nonlinear system isapproximated by a finite-order Volterra series. The original nonlinear system is replaced by a bilinear system in order to determine the kernels of this
Diagnostic Approach to Functional Recovery
DEFF Research Database (Denmark)
Havsteen, Inger; Madsen, Kristoffer H; Christensen, Hanne Krarup
2013-01-01
available and does not pose any adverse effects, repeated fMRI measurements provide unprecedented possibilities to prospectively assess the time course of reorganization in functional neural networks after stroke and relate the temporospatial dynamics of reorganization at the systems level to functional...
Energy Technology Data Exchange (ETDEWEB)
Al-Hawat, Sh; Naddaf, M [Physics Department, Atomic Energy Commission, PO Box 6091, Damascus (Syrian Arab Republic)
2005-04-21
The electron energy distribution function (EEDF) was determined from the second derivative of the I-V Langmuir probe characteristics and, thereafter, theoretically calculated by solving the plasma kinetic equation, using the black wall (BW) approximation, in the positive column of a neon glow discharge. The pressure has been varied from 0.5 to 4 Torr and the current from 10 to 30 mA. The measured electron temperature, density and electric field strength were used as input data for solving the kinetic equation. Comparisons were made between the EEDFs obtained from experiment, the BW approach, the Maxwellian distribution and the Rutcher solution of the kinetic equation in the elastic energy range. The best conditions for the BW approach are found to be under the discharge conditions: current density j{sub d} = 4.45 mA cm{sup -2} and normalized electric field strength E/p = 1.88 V cm{sup -1} Torr{sup -1}.
Neese, Frank; Wennmohs, Frank; Hansen, Andreas
2009-03-21
Coupled-electron pair approximations (CEPAs) and coupled-pair functionals (CPFs) have been popular in the 1970s and 1980s and have yielded excellent results for small molecules. Recently, interest in CEPA and CPF methods has been renewed. It has been shown that these methods lead to competitive thermochemical, kinetic, and structural predictions. They greatly surpass second order Moller-Plesset and popular density functional theory based approaches in accuracy and are intermediate in quality between CCSD and CCSD(T) in extended benchmark studies. In this work an efficient production level implementation of the closed shell CEPA and CPF methods is reported that can be applied to medium sized molecules in the range of 50-100 atoms and up to about 2000 basis functions. The internal space is spanned by localized internal orbitals. The external space is greatly compressed through the method of pair natural orbitals (PNOs) that was also introduced by the pioneers of the CEPA approaches. Our implementation also makes extended use of density fitting (or resolution of the identity) techniques in order to speed up the laborious integral transformations. The method is called local pair natural orbital CEPA (LPNO-CEPA) (LPNO-CPF). The implementation is centered around the concepts of electron pairs and matrix operations. Altogether three cutoff parameters are introduced that control the size of the significant pair list, the average number of PNOs per electron pair, and the number of contributing basis functions per PNO. With the conservatively chosen default values of these thresholds, the method recovers about 99.8% of the canonical correlation energy. This translates to absolute deviations from the canonical result of only a few kcal mol(-1). Extended numerical test calculations demonstrate that LPNO-CEPA (LPNO-CPF) has essentially the same accuracy as parent CEPA (CPF) methods for thermochemistry, kinetics, weak interactions, and potential energy surfaces but is up to 500
A Padé approximant approach to two kinds of transcendental equations with applications in physics
International Nuclear Information System (INIS)
Luo, Qiang; Wang, Zhidan; Han, Jiurong
2015-01-01
In this paper, we obtain the analytical solutions of two kinds of transcendental equations with numerous applications in college physics by means of the Lagrange inversion theorem. Afterwards we rewrite them in the form of a ratio of rational polynomials by a second-order Padé approximant from a practical and instructional perspective. Our method is illustrated in a pedagogical manner for the benefit of students at the undergraduate level. The approximate formulas introduced in the paper can be applied to abundant examples in physics textbooks, such as Fraunhofer single-slit diffraction, Wien’s displacement law, and the Schrödinger equation with single- or double-δ potential. These formulas, consequently, can reach considerable accuracies according to the numerical results; therefore, they promise to act as valuable ingredients in the standard teaching curriculum. (paper)
An intrinsic robust rank-one-approximation approach for currencyportfolio optimization
Hongxuan Huang; Zhengjun Zhang
2018-01-01
A currency portfolio is a special kind of wealth whose value fluctuates with foreignexchange rates over time, which possesses 3Vs (volume, variety and velocity) properties of big datain the currency market. In this paper, an intrinsic robust rank one approximation (ROA) approachis proposed to maximize the value of currency portfolios over time. The main results of the paperinclude four parts: Firstly, under the assumptions about the currency market, the currency portfoliooptimization problem ...
Transient management using the safety function approach
International Nuclear Information System (INIS)
Corcoran, W.R.; Barrow, J.H.; Bischoff, G.C.; Callaghan, V.M.; Pearce, R.T.
1984-01-01
The safety function approach is described. Its use in the development of a transient management procedures system includes optimal recovery procedures tailored to specific, anticipated symptom sets and a functional recovery procedure which is more general. Simulator evaluations are described
International Nuclear Information System (INIS)
Palma, Daniel A.; Goncalves, Alessandro C.; Martinez, Aquilino S.; Silva, Fernando C.
2008-01-01
The activation technique allows much more precise measurements of neutron intensity, relative or absolute. The technique requires the knowledge of the Doppler broadening function ψ(x,ξ) to determine the resonance self-shielding factors in the epithermal range G epi (τ,ξ). Two new analytical approximations for the Doppler broadening function ψ(x,ξ) are proposed. The approximations proposed are compared with other methods found in literature for the calculation of the ψ(x,ξ) function, that is, the 4-pole Pade method and the Frobenius method, when applied to the calculation of G epi (τ,ξ). The results obtained provided satisfactory accuracy. (authors)
DEFF Research Database (Denmark)
Shuai, Hang; Ai, Xiaomeng; Wen, Jinyu
2017-01-01
This paper proposes a hybrid approximate dynamic programming (ADP) approach for the multiple time-period optimal power flow in integrated gas and power systems. ADP successively solves Bellman's equation to make decisions according to the current state of the system. So, the updated near future...
Directory of Open Access Journals (Sweden)
Ishak Altun
2016-01-01
Full Text Available We provide sufficient conditions for the existence of a unique common fixed point for a pair of mappings T,S:X→X, where X is a nonempty set endowed with a certain metric. Moreover, a numerical algorithm is presented in order to approximate such solution. Our approach is different to the usual used methods in the literature.
Energy Technology Data Exchange (ETDEWEB)
Larin, S.A.; Ritbergen, T. van; Vermaseren, J.A.M.
1993-12-01
We obtain the analytic next-next-to-leading perturbative QCD corrections in the leading twist approximation for the moments N = 2, 4, 6, 8 of the non-singlet deep inelastic structure functions F{sub 2} and F{sub L}. We calculate the three-loop anomalous dimensions of the corresponding non-singlet operators and the three-loop coefficient functions of the structure function F{sub L}. (orig.).
International Nuclear Information System (INIS)
Larin, S.A.; Ritbergen, T. van; Vermaseren, J.A.M.
1993-12-01
We obtain the analytic next-next-to-leading perturbative QCD corrections in the leading twist approximation for the moments N = 2, 4, 6, 8 of the non-singlet deep inelastic structure functions F 2 and F L . We calculate the three-loop anomalous dimensions of the corresponding non-singlet operators and the three-loop coefficient functions of the structure function F L . (orig.)
Gabor, A.F.; Ommeren, van J.C.W.
2006-01-01
In this article we focus on approximation algorithms for facility location problems with subadditive costs. As examples of such problems, we present three facility location problems with stochastic demand and exponential servers, respectively inventory. We present a (1+e,1)-reduction of the facility
Gabor, Adriana F.; van Ommeren, Jan C.W.
2006-01-01
In this article we focus on approximation algorithms for facility location problems with subadditive costs. As examples of such problems, we present three facility location problems with stochastic demand and exponential servers, respectively inventory. We present a $(1+\\varepsilon, 1)$-reduction of
Approximation algorithms for facility location problems with discrete subadditive cost functions
Gabor, A.F.; van Ommeren, Jan C.W.
2005-01-01
In this article we focus on approximation algorithms for facility location problems with subadditive costs. As examples of such problems, we present two facility location problems with stochastic demand and exponential servers, respectively inventory. We present a $(1+\\epsilon,1)$- reduction of the
International Nuclear Information System (INIS)
Tang Xiangyang; Hsieh Jiang
2007-01-01
A cone-angle-based window function is defined in this manuscript for image reconstruction using helical cone beam filtered backprojection (CB-FBP) algorithms. Rather than defining the window boundaries in a two-dimensional detector acquiring projection data for computed tomographic imaging, the cone-angle-based window function deals with data redundancy by selecting rays with the smallest cone angle relative to the reconstruction plane. To be computationally efficient, an asymptotic approximation of the cone-angle-based window function is also given and analyzed in this paper. The benefit of using such an asymptotic approximation also includes the avoidance of functional discontinuities that cause artifacts in reconstructed tomographic images. The cone-angle-based window function and its asymptotic approximation provide a way, equivalent to the Tam-Danielsson-window, for helical CB-FBP reconstruction algorithms to deal with data redundancy, regardless of where the helical pitch is constant or dynamically variable during a scan. By taking the cone-parallel geometry as an example, a computer simulation study is conducted to evaluate the proposed window function and its asymptotic approximation for helical CB-FBP reconstruction algorithm to handle data redundancy. The computer simulated Forbild head and thorax phantoms are utilized in the performance evaluation, showing that the proposed cone-angle-based window function and its asymptotic approximation can deal with data redundancy very well in cone beam image reconstruction from projection data acquired along helical source trajectories. Moreover, a numerical study carried out in this paper reveals that the proposed cone-angle-based window function is actually equivalent to the Tam-Danielsson-window, and rigorous mathematical proofs are being investigated
Approximate entropy: a new evaluation approach of mental workload under multitask conditions
Yao, Lei; Li, Xiaoling; Wang, Wei; Dong, Yuanzhe; Jiang, Ying
2014-04-01
There are numerous instruments and an abundance of complex information in the traditional cockpit display-control system, and pilots require a long time to familiarize themselves with the cockpit interface. This can cause accidents when they cope with emergency events, suggesting that it is necessary to evaluate pilot cognitive workload. In order to establish a simplified method to evaluate cognitive workload under a multitask condition. We designed a series of experiments involving different instrument panels and collected electroencephalograms (EEG) from 10 healthy volunteers. The data were classified and analyzed with an approximate entropy (ApEn) signal processing. ApEn increased with increasing experiment difficulty, suggesting that it can be used to evaluate cognitive workload. Our results demonstrate that ApEn can be used as an evaluation criteria of cognitive workload and has good specificity and sensitivity. Moreover, we determined an empirical formula to assess the cognitive workload interval, which can simplify cognitive workload evaluation under multitask conditions.
Energy Technology Data Exchange (ETDEWEB)
Palma, Daniel A.P. [Centro Federal de Educacao Tecnologica de Quimica de Nilopolis/RJ (CEFET), RJ (Brazil)]. E-mail: dpalma@cefeteq.br; Martinez, Aquilino S.; Silva, Fernando C. [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia. Programa de Engenharia Nuclear]. E-mail: aquilino@lmp.ufrj.br; fernando@lmn.con.ufrj.br
2005-07-01
An analytical approximation of the Doppler broadening function {psi}(x,{xi}) is proposed. This approximation is based on the solution of the differential equation for {psi}(x,{xi}) using the methods of Frobenius and the parameters variation. The analytical form derived for {psi}(x,{xi}) in terms of elementary functions is very simple and precise. It can be useful for applications related to the treatment of nuclear resonances mainly for the calculations of multigroup parameters and self-protection factors of the resonances, being the last used to correct microscopic cross-sections measurements by the activation technique. (author)
Multiconfigurational Green's function approaches in quantum chemistry
International Nuclear Information System (INIS)
Yeager, D.L.
1984-01-01
The author discusses multiconfigurational Green's function techniques and generalizations. In particular he is interested in developing and applying these techniques for isolated atoms and small molecules. Furthermore, he develops formalisms that are fairly clear, accurate, and capable of being applied to open-shell and highly-correlated systems as well as to closed-shell systems with little electronic correlation. The two kinds of Green's functions that this article discusses are the single-particle Green's function and the retarded two-time Green's function in the energy representation. The poles of the former give the ionization potentials and electron affinities while the poles of the latter give the excitation energies. The multiconfigurational approximations are known as the multiconfigurational electron propagator (MCEP) and the multiconfigurational time-dependent Hartree-Fock (MCTDHF) (also known as the multiconfigurational random phase approximation (MCRPA) or the multiconfigurational linear response), respectively. 44 references
Functional renormalization group approach to the two dimensional Bose gas
Energy Technology Data Exchange (ETDEWEB)
Sinner, A; Kopietz, P [Institut fuer Theoretische Physik, Universitaet Frankfurt, Max-von-Laue Strasse 1, 60438 Frankfurt (Germany); Hasselmann, N [International Center for Condensed Matter Physics, Universidade de BrasIlia, Caixa Postal 04667, 70910-900 BrasIlia, DF (Brazil)], E-mail: hasselma@itp.uni-frankfurt.de, E-mail: sinner@itp.uni-frankfurt.de
2009-02-01
We investigate the small frequency and momentum structure of the weakly interacting Bose gas in two dimensions using a functional renormalization group approach. The flow equations are derived within a derivative approximation of the effective action up to second order in spatial and temporal variables and investigated numerically. The truncation we employ is based on the perturbative structure of the theory and is well described as a renormalization group enhanced perturbation theory. It allows to calculate corrections to the Bogoliubov spectrum and to investigate the damping of quasiparticles. Our approach allows to circumvent the divergences which plague the usual perturbative approach.
Perlt, Eva; Ray, Promit; Hansen, Andreas; Malberg, Friedrich; Grimme, Stefan; Kirchner, Barbara
2018-05-01
Ionic liquids raise interesting but complicated questions for theoretical investigations due to the fact that a number of different inter-molecular interactions, e.g., hydrogen bonding, long-range Coulomb interactions, and dispersion interactions, need to be described properly. Here, we present a detailed study on the ionic liquids ethylammonium nitrate and 1-ethyl-3-methylimidazolium acetate, in which we compare different dispersion corrected density functional approximations to accurate local coupled cluster data in static calculations on ionic liquid clusters. The efficient new composite method B97-3c is tested and has been implemented in CP2K for future studies. Furthermore, tight-binding based approaches which may be used in large scale simulations are assessed. Subsequently, ab initio as well as classical molecular dynamics simulations are conducted and structural analyses are presented in order to shed light on the different short- and long-range structural patterns depending on the method and the system size considered in the simulation. Our results indicate the presence of strong hydrogen bonds in ionic liquids as well as the aggregation of alkyl side chains due to dispersion interactions.
International Nuclear Information System (INIS)
Johnson, E.
1977-01-01
A theory for site-site pair distribution functions of molecular fluids is derived from the Ornstein-Zernike equation. Atom-atom pair distribution functions of this theory which were obtained by using different approximations for the Percus-Yevick site-site direct correlation functions are compared
1989-10-31
fo tmaa OmfuogeM ara Mmi. fal in fM?05V~ ~ ~ ~ ~ ~ A D A 2 4 0409"~ n ugt Psoo,@’ oducbof Proton (07044 136M. WagaWapN. DC 20141 T1 3. REPORT TYPE...Al (circumscription, non- monotonic reasoning, and default reasoning), our approach is based on fuzzy logic and, more specifically, on the theory of
Frydel, Derek; Ma, Manman
2016-06-01
Using the adiabatic connection, we formulate the free energy in terms of the correlation function of a fictitious system, h_{λ}(r,r^{'}), in which interactions λu(r,r^{'}) are gradually switched on as λ changes from 0 to 1. The function h_{λ}(r,r^{'}) is then obtained from the inhomogeneous Ornstein-Zernike equation and the two equations constitute a general liquid-state framework for treating inhomogeneous fluids. The two equations do not yet constitute a closed set. In the present work we use the closure c_{λ}(r,r^{'})≈-λβu(r,r^{'}), known as the random-phase approximation (RPA). We demonstrate that the RPA is identical with the variational Gaussian approximation derived within the field-theoretical framework, originally derived and used for charged particles. We apply our generalized RPA approximation to the Gaussian core model and Coulomb charges.
International Nuclear Information System (INIS)
Song Lina; Wang Weiguo
2010-01-01
In this Letter, an enhanced Adomian decomposition method which introduces the h-curve of the homotopy analysis method into the standard Adomian decomposition method is proposed. Some examples prove that this method can derive successfully approximate rational Jacobi elliptic function solutions of the fractional differential equations.
International Nuclear Information System (INIS)
Lublinsky, M.
2004-01-01
A simple analytic expression for the non-singlet structure function fns is given. The expression is derived from the result of B. I. Ermolaev et al. (1996) obtained by low x resummation of the quark ladder diagrams in the double logarithmic approximation of perturbative QCD. (orig.)
Rosolen, A.; Peco, C.; Arroyo, M.
2013-01-01
We present an adaptive meshfree method to approximate phase-field models of biomembranes. In such models, the Helfrich curvature elastic energy, the surface area, and the enclosed volume of a vesicle are written as functionals of a continuous phase-field, which describes the interface in a smeared manner. Such functionals involve up to second-order spatial derivatives of the phase-field, leading to fourth-order Euler–Lagrange partial differential equations (PDE). The solutions develop sharp i...
Csordás, András; Graham, Robert; Szépfalusy, Péter
1997-01-01
The Bogoliubov equations of the quasi-particle excitations in a weakly interacting trapped Bose-condensate are solved in the WKB approximation in an isotropic harmonic trap, determining the discrete quasi-particle energies and wave functions by torus (Bohr-Sommerfeld) quantization of the integrable classical quasi-particle dynamics. The results are used to calculate the position and strengths of the peaks in the dynamic structure function which can be observed by off-resonance inelastic light...
Uniform approximations of Bernoulli and Euler polynomials in terms of hyperbolic functions
J.L. López; N.M. Temme (Nico)
1998-01-01
textabstractBernoulli and Euler polynomials are considered for large values of the order. Convergent expansions are obtained for $B_n(nz+1/2)$ and $E_n(nz+1/2)$ in powers of $n^{-1$, with coefficients being rational functions of $z$ and hyperbolic functions of argument $1/2z$. These expansions are
International Nuclear Information System (INIS)
Jung, J.; Alvarellos, J.E.; Garcia-Gonzalez, P.; Godby, R.W.
2004-01-01
The complex nature of electron-electron correlations is made manifest in the very simple but nontrivial problem of two electrons confined within a sphere. The description of highly nonlocal correlation and self-interaction effects by widely used local and semilocal exchange-correlation energy density functionals is shown to be unsatisfactory in most cases. Even the best such functionals exhibit significant errors in the Kohn-Sham potentials and density profiles
Directory of Open Access Journals (Sweden)
Fernando Racimo
2014-11-01
Full Text Available Quantifying the proportion of polymorphic mutations that are deleterious or neutral is of fundamental importance to our understanding of evolution, disease genetics and the maintenance of variation genome-wide. Here, we develop an approximation to the distribution of fitness effects (DFE of segregating single-nucleotide mutations in humans. Unlike previous methods, we do not assume that synonymous mutations are neutral or not strongly selected, and we do not rely on fitting the DFE of all new nonsynonymous mutations to a single probability distribution, which is poorly motivated on a biological level. We rely on a previously developed method that utilizes a variety of published annotations (including conservation scores, protein deleteriousness estimates and regulatory data to score all mutations in the human genome based on how likely they are to be affected by negative selection, controlling for mutation rate. We map this and other conservation scores to a scale of fitness coefficients via maximum likelihood using diffusion theory and a Poisson random field model on SNP data. Our method serves to approximate the deleterious DFE of mutations that are segregating, regardless of their genomic consequence. We can then compare the proportion of mutations that are negatively selected or neutral across various categories, including different types of regulatory sites. We observe that the distribution of intergenic polymorphisms is highly peaked at neutrality, while the distribution of nonsynonymous polymorphisms has a second peak at [Formula: see text]. Other types of polymorphisms have shapes that fall roughly in between these two. We find that transcriptional start sites, strong CTCF-enriched elements and enhancers are the regulatory categories with the largest proportion of deleterious polymorphisms.
Energy Technology Data Exchange (ETDEWEB)
Palma, Daniel A. [CEFET QUIMICA de Nilopolis/RJ, Rio de Janeiro (Brazil); Goncalves, Alessandro C.; Martinez, Aquilino S.; Silva, Fernando C. [COPPE/UFRJ - Programa de Engenharia Nuclear, Rio de Janeiro (Brazil)
2008-07-01
The activation technique allows much more precise measurements of neutron intensity, relative or absolute. The technique requires the knowledge of the Doppler broadening function psi(x,xi) to determine the resonance self-shielding factors in the epithermal range G{sub epi} (tau,xi). Two new analytical approximations for the Doppler broadening function psi(x,xi) are proposed. The approximations proposed are compared with other methods found in literature for the calculation of the psi(x,xi) function, that is, the 4-pole Pade method and the Frobenius method, when applied to the calculation of G{sub epi} (tau,xi). The results obtained provided satisfactory accuracy. (authors)
Energy Technology Data Exchange (ETDEWEB)
Nakano, Masayoshi, E-mail: mnaka@cheng.es.osaka-u.ac.jp; Minami, Takuya, E-mail: mnaka@cheng.es.osaka-u.ac.jp; Fukui, Hitoshi, E-mail: mnaka@cheng.es.osaka-u.ac.jp; Yoneda, Kyohei, E-mail: mnaka@cheng.es.osaka-u.ac.jp; Shigeta, Yasuteru, E-mail: mnaka@cheng.es.osaka-u.ac.jp; Kishi, Ryohei, E-mail: mnaka@cheng.es.osaka-u.ac.jp [Department of Materials Engineering Science, Graduate School of Engineering Science, Osaka University, Toyonaka, Osaka 560-8531 (Japan); Champagne, Benoît; Botek, Edith [Laboratoire de Chimie Théorique, Facultés Universitaires Notre-Dame de la Paix (FUNDP), rue de Bruxelles, 61, 5000 Namur (Belgium)
2015-01-22
We develop a novel method for the calculation and the analysis of the one-electron reduced densities in open-shell molecular systems using the natural orbitals and approximate spin projected occupation numbers obtained from broken symmetry (BS), i.e., spin-unrestricted (U), density functional theory (DFT) calculations. The performance of this approximate spin projection (ASP) scheme is examined for the diradical character dependence of the second hyperpolarizability (γ) using several exchange-correlation functionals, i.e., hybrid and long-range corrected UDFT schemes. It is found that the ASP-LC-UBLYP method with a range separating parameter μ = 0.47 reproduces semi-quantitatively the strongly-correlated [UCCSD(T)] result for p-quinodimethane, i.e., the γ variation as a function of the diradical character.
Li, Zhendong; Liu, Wenjian
2010-08-14
The spin-adaptation of single-reference quantum chemical methods for excited states of open-shell systems has been nontrivial. The primary reason is that the configuration space, generated by a truncated rank of excitations from only one component of a reference multiplet, is spin-incomplete. Those "missing" configurations are of higher ranks and can, in principle, be recaptured by a particular class of excitation operators. However, the resulting formalisms are then quite involved and there are situations [e.g., time-dependent density functional theory (TD-DFT) under the adiabatic approximation] that prevent one from doing so. To solve this issue, we propose here a tensor-coupling scheme that invokes all the components of a reference multiplet (i.e., a tensor reference) rather than increases the excitation ranks. A minimal spin-adapted n-tuply excited configuration space can readily be constructed by tensor products between the n-tuple tensor excitation operators and the chosen tensor reference. Further combined with the tensor equation-of-motion formalism, very compact expressions for excitation energies can be obtained. As a first application of this general idea, a spin-adapted open-shell random phase approximation is first developed. The so-called "translation rule" is then adopted to formulate a spin-adapted, restricted open-shell Kohn-Sham (ROKS)-based TD-DFT (ROKS-TD-DFT). Here, a particular symmetry structure has to be imposed on the exchange-correlation kernel. While the standard ROKS-TD-DFT can access only excited states due to singlet-coupled single excitations, i.e., only some of the singly excited states of the same spin (S(i)) as the reference, the new scheme can capture all the excited states of spin S(i)-1, S(i), or S(i)+1 due to both singlet- and triplet-coupled single excitations. The actual implementation and computation are very much like the (spin-contaminated) unrestricted Kohn-Sham-based TD-DFT. It is also shown that spin-contaminated spin
Functional integral approach to classical statistical dynamics
International Nuclear Information System (INIS)
Jensen, R.V.
1980-04-01
A functional integral method is developed for the statistical solution of nonlinear stochastic differential equations which arise in classical dynamics. The functional integral approach provides a very natural and elegant derivation of the statistical dynamical equations that have been derived using the operator formalism of Martin, Siggia, and Rose
Approximation of Mixed-Type Functional Equations in Menger PN-Spaces
Directory of Open Access Journals (Sweden)
M. Eshaghi Gordji
2012-01-01
Full Text Available Let X and Y be vector spaces. We show that a function f:X→Y with f(0=0 satisfies Δf(x1,…,xn=0 for all x1,…,xn∈X, if and only if there exist functions C:X×X×X→Y, B:X×X→Y and A:X→Y such that f(x=C(x,x,x+B(x,x+A(x for all x∈X, where the function C is symmetric for each fixed one variable and is additive for fixed two variables, B is symmetric bi-additive, A is additive and Δf(x1,…,xn=∑k=2n(∑i1=2k∑i2=i1+1k+1⋯∑in-k+1=in-k+1nf(∑i=1,i≠i1,…,in-k+1nxi-∑r=1n-k+1xir+f(∑i=1nxi-2n-2∑i=2n(f(x1+xi+f(x1-xi+2n-1(n-2f(x1 (n∈N, n≥3 for all x1,…,xn∈X. Furthermore, we solve the stability problem for a given function f satisfying Δf(x1,…,xn=0, in the Menger probabilistic normed spaces.
Kryven, I.; Röblitz, S; Schütte, C.
2015-01-01
Background: The chemical master equation is the fundamental equation of stochastic chemical kinetics. This differential-difference equation describes temporal evolution of the probability density function for states of a chemical system. A state of the system, usually encoded as a vector, represents
International Nuclear Information System (INIS)
Khan, S.H.; Ivanov, A.A.
1993-01-01
This paper describes an approximate method for calculating the static characteristics of linear step motors (LSM), being developed for control rod drives (CRD) in large nuclear reactors. The static characteristic of such an LSM which is given by the variation of electromagnetic force with armature displacement determines the motor performance in its standing and dynamic modes. The approximate method of calculation of these characteristics is based on the permeance analysis method applied to the phase magnetic circuit of LSM. This is a simple, fast and efficient analytical approach which gives satisfactory results for small stator currents and weak iron saturation, typical to the standing mode of operation of LSM. The method is validated by comparing theoretical results with experimental ones. (Author)
An inverse approach for elucidating dendritic function
Directory of Open Access Journals (Sweden)
Benjamin Torben-Nielsen
2010-09-01
Full Text Available We outline an inverse approach for investigating dendritic function-structure relationships by optimizing dendritic trees for a-priori chosen computational functions. The inverse approach can be applied in two different ways. First, we can use it as a `hypothesis generator' in which we optimize dendrites for a function of general interest. The optimization yields an artificial dendrite that is subsequently compared to real neurons. This comparison potentially allows us to propose hypotheses about the function of real neurons. In this way, we investigated dendrites that optimally perform input-order detection. Second, we can use it as a `function confirmation' by optimizing dendrites for functions hypothesized to be performed by classes of neurons. If the optimized, artificial, dendrites resemble the dendrites of real neurons the artificial dendrites corroborate the hypothesized function of the real neuron. Moreover, properties of the artificial dendrites can lead to predictions about yet unmeasured properties. In this way, we investigated wide-field motion integration performed by the VS cells of the fly visual system. In outlining the inverse approach and two applications, we also elaborate on the nature of dendritic function. We furthermore discuss the role of optimality in assigning functions to dendrites and point out interesting future directions.
Quantum functional analysis non-coordinate approach
Helemskii, A Ya
2010-01-01
This book contains a systematic presentation of quantum functional analysis, a mathematical subject also known as operator space theory. Created in the 1980s, it nowadays is one of the most prominent areas of functional analysis, both as a field of active research and as a source of numerous important applications. The approach taken in this book differs significantly from the standard approach used in studying operator space theory. Instead of viewing "quantized coefficients" as matrices in a fixed basis, in this book they are interpreted as finite rank operators in a fixed Hilbert space. This allows the author to replace matrix computations with algebraic techniques of module theory and tensor products, thus achieving a more invariant approach to the subject. The book can be used by graduate students and research mathematicians interested in functional analysis and related areas of mathematics and mathematical physics. Prerequisites include standard courses in abstract algebra and functional analysis.
Directory of Open Access Journals (Sweden)
Hozejowski Leszek
2012-04-01
Full Text Available The paper is devoted to a computational problem of predicting a local heat transfer coefficient from experimental temperature data. The experimental part refers to boiling flow of a refrigerant in a minichannel. Heat is dissipated from heating alloy to the flowing liquid due to forced convection. The mathematical model of the problem consists of the governing Poisson equation and the proper boundary conditions. For accurate results it is required to smooth the measurements which was obtained by using Trefftz functions. The measurements were approximated with a linear combination of Trefftz functions. Due to the computational procedure in which the measurement errors are known, it was possible to smooth the data and also to reduce the residuals of approximation on the boundaries.
Amin, Talha
2013-01-01
In the paper, we present a comparison of dynamic programming and greedy approaches for construction and optimization of approximate decision rules relative to the number of misclassifications. We use an uncertainty measure that is a difference between the number of rows in a decision table T and the number of rows with the most common decision for T. For a nonnegative real number γ, we consider γ-decision rules that localize rows in subtables of T with uncertainty at most γ. Experimental results with decision tables from the UCI Machine Learning Repository are also presented. © 2013 Springer-Verlag.
A New Approach to Rational Discrete-Time Approximations to Continuous-Time Fractional-Order Systems
Matos , Carlos; Ortigueira , Manuel ,
2012-01-01
Part 10: Signal Processing; International audience; In this paper a new approach to rational discrete-time approximations to continuous fractional-order systems of the form 1/(sα+p) is proposed. We will show that such fractional-order LTI system can be decomposed into sub-systems. One has the classic behavior and the other is similar to a Finite Impulse Response (FIR) system. The conversion from continuous-time to discrete-time systems will be done using the Laplace transform inversion integr...
Short-distance behavior of the Bethe--Salpeter wave function in the ladder approximation
International Nuclear Information System (INIS)
Guth, A.H.; Soper, D.E.
1975-01-01
We investigate the short-distance behavior of the (Wick-rotated) Bethe--Salpeter wave function for the two spin-1/2 quarks bound by the exchange of a massive vector meson. We use the ladder-model kernel, which has the same p -4 scaling behavior as the true kernel in a theory with a fixed point of the renormalization group at g not equal to 0. For a bound state with the quantum numbers of the pion, the leading asymptotic behavior is chi (q/sup μ/) approx. cq/sup -4 + epsilon(g)/γ 5 , where epsilon (g) =1- (1-g 2 /π 2 ) 1 / 2 . Our method also provides the full asymptotic series, although it should be noted that the nonleading terms will depend on the nonleading behavior of the ladder-model kernel. A general term has the form cq - /sup a/(lnq)/sup n/phi (q/sup μ/), where c is an unknown constant, a may be integral or nonintegral, n is an integer, and phi (q/sup μ/) is a representation function of the rotation group in four dimensions
Li, Chen; Requist, Ryan; Gross, E. K. U.
2018-02-01
We perform model calculations for a stretched LiF molecule, demonstrating that nonadiabatic charge transfer effects can be accurately and seamlessly described within a density functional framework. In alkali halides like LiF, there is an abrupt change in the ground state electronic distribution due to an electron transfer at a critical bond length R = Rc, where an avoided crossing of the lowest adiabatic potential energy surfaces calls the validity of the Born-Oppenheimer approximation into doubt. Modeling the R-dependent electronic structure of LiF within a two-site Hubbard model, we find that nonadiabatic electron-nuclear coupling produces a sizable elongation of the critical Rc by 0.5 bohr. This effect is very accurately captured by a simple and rigorously derived correction, with an M-1 prefactor, to the exchange-correlation potential in density functional theory, M = reduced nuclear mass. Since this nonadiabatic term depends on gradients of the nuclear wave function and conditional electronic density, ∇Rχ(R) and ∇Rn(r, R), it couples the Kohn-Sham equations at neighboring R points. Motivated by an observed localization of nonadiabatic effects in nuclear configuration space, we propose a local conditional density approximation—an approximation that reduces the search for nonadiabatic density functionals to the search for a single function y(n).
Directory of Open Access Journals (Sweden)
Jiameng Wu
2018-01-01
Full Text Available The infinite depth free surface Green function (GF and its high order derivatives for diffraction and radiation of water waves are considered. Especially second order derivatives are essential requirements in high-order panel method. In this paper, concerning the classical representation, composed of a semi-infinite integral involving a Bessel function and a Cauchy singularity, not only the GF and its first order derivatives but also second order derivatives are derived from four kinds of analytical series expansion and refined division of whole calculation domain. The approximations of special functions, particularly the hypergeometric function and the algorithmic applicability with different subdomains are implemented. As a result, the computation accuracy can reach 10-9 in whole domain compared with conventional methods based on direct numerical integration. Furthermore, numerical efficiency is almost equivalent to that with the classical method.
Directory of Open Access Journals (Sweden)
Yanqi Hao
2015-07-01
Full Text Available Alternative splicing acts on transcripts from almost all human multi-exon genes. Notwithstanding its ubiquity, fundamental ramifications of splicing on protein expression remain unresolved. The number and identity of spliced transcripts that form stably folded proteins remain the sources of considerable debate, due largely to low coverage of experimental methods and the resulting absence of negative data. We circumvent this issue by developing a semi-supervised learning algorithm, positive unlabeled learning for splicing elucidation (PULSE; http://www.kimlab.org/software/pulse, which uses 48 features spanning various categories. We validated its accuracy on sets of bona fide protein isoforms and directly on mass spectrometry (MS spectra for an overall AU-ROC of 0.85. We predict that around 32% of “exon skipping” alternative splicing events produce stable proteins, suggesting that the process engenders a significant number of previously uncharacterized proteins. We also provide insights into the distribution of positive isoforms in various functional classes and into the structural effects of alternative splicing.
Estimating variability in functional images using a synthetic resampling approach
International Nuclear Information System (INIS)
Maitra, R.; O'Sullivan, F.
1996-01-01
Functional imaging of biologic parameters like in vivo tissue metabolism is made possible by Positron Emission Tomography (PET). Many techniques, such as mixture analysis, have been suggested for extracting such images from dynamic sequences of reconstructed PET scans. Methods for assessing the variability in these functional images are of scientific interest. The nonlinearity of the methods used in the mixture analysis approach makes analytic formulae for estimating variability intractable. The usual resampling approach is infeasible because of the prohibitive computational effort in simulating a number of sinogram. datasets, applying image reconstruction, and generating parametric images for each replication. Here we introduce an approach that approximates the distribution of the reconstructed PET images by a Gaussian random field and generates synthetic realizations in the imaging domain. This eliminates the reconstruction steps in generating each simulated functional image and is therefore practical. Results of experiments done to evaluate the approach on a model one-dimensional problem are very encouraging. Post-processing of the estimated variances is seen to improve the accuracy of the estimation method. Mixture analysis is used to estimate functional images; however, the suggested approach is general enough to extend to other parametric imaging methods
Approximate Dynamic Programming: Combining Regional and Local State Following Approximations.
Deptula, Patryk; Rosenfeld, Joel A; Kamalapurkar, Rushikesh; Dixon, Warren E
2018-06-01
An infinite-horizon optimal regulation problem for a control-affine deterministic system is solved online using a local state following (StaF) kernel and a regional model-based reinforcement learning (R-MBRL) method to approximate the value function. Unlike traditional methods such as R-MBRL that aim to approximate the value function over a large compact set, the StaF kernel approach aims to approximate the value function in a local neighborhood of the state that travels within a compact set. In this paper, the value function is approximated using a state-dependent convex combination of the StaF-based and the R-MBRL-based approximations. As the state enters a neighborhood containing the origin, the value function transitions from being approximated by the StaF approach to the R-MBRL approach. Semiglobal uniformly ultimately bounded (SGUUB) convergence of the system states to the origin is established using a Lyapunov-based analysis. Simulation results are provided for two, three, six, and ten-state dynamical systems to demonstrate the scalability and performance of the developed method.
A Functional Approach to User Guides
DEFF Research Database (Denmark)
Nielsen, Sandro
2007-01-01
to fulfil the requirements of users. By applying the functional approach lexicographers are forced to reconsider the scope of the user guide. The user guide has traditionally centred on the structures of entries - and consequently on the word list - but its scope should be widened, so as to include all......The functional approach opens up exciting new possibilities for theoretical and practical lexicography. It encourages lexicographers to adopt a new way of thinking when planning and compiling dictionaries and when discussing and developing new lexicographic principles. One area in which it impacts...... on lexicography and lexicographic products is the writing of a really crafted and valuable user guide for instance by giving increased consideration to the user perspective. This involves the identification of the functions of the dictionary in terms of communication-oriented and cognitive functions, which helps...
International Nuclear Information System (INIS)
Frishman, A.; Hoffman, D.K.; Kouri, D.J.
1997-01-01
We report a distributed approximating functional (DAF) fit of the ab initio potential-energy data of Liu [J. Chem. Phys. 58, 1925 (1973)] and Siegbahn and Liu [ibid. 68, 2457 (1978)]. The DAF-fit procedure is based on a variational principle, and is systematic and general. Only two adjustable parameters occur in the DAF leading to a fit which is both accurate (to the level inherent in the input data; RMS error of 0.2765 kcal/mol) and smooth (open-quotes well-tempered,close quotes in DAF terminology). In addition, the LSTH surface of Truhlar and Horowitz based on this same data [J. Chem. Phys. 68, 2466 (1978)] is itself approximated using only the values of the LSTH surface on the same grid coordinate points as the ab initio data, and the same DAF parameters. The purpose of this exercise is to demonstrate that the DAF delivers a well-tempered approximation to a known function that closely mimics the true potential-energy surface. As is to be expected, since there is only roundoff error present in the LSTH input data, even more significant figures of fitting accuracy are obtained. The RMS error of the DAF fit, of the LSTH surface at the input points, is 0.0274 kcal/mol, and a smooth fit, accurate to better than 1cm -1 , can be obtained using more than 287 input data points. copyright 1997 American Institute of Physics
Gauss-Arnoldi quadrature for -1φ,φ> and rational Pade-type approximation for Markov-type functions
International Nuclear Information System (INIS)
Knizhnerman, L A
2008-01-01
The efficiency of Gauss-Arnoldi quadrature for the calculation of the quantity -1 φ,φ> is studied, where A is a bounded operator in a Hilbert space and φ is a non-trivial vector in this space. A necessary and a sufficient conditions are found for the efficiency of the quadrature in the case of a normal operator. An example of a non-normal operator for which this quadrature is inefficient is presented. It is shown that Gauss-Arnoldi quadrature is related in certain cases to rational Pade-type approximation (with the poles at Ritz numbers) for functions of Markov type and, in particular, can be used for the localization of the poles of a rational perturbation. Error estimates are found, which can also be used when classical Pade approximation does not work or it may not be efficient. Theoretical results and conjectures are illustrated by numerical experiments. Bibliography: 44 titles
Fujiwara, Takeo; Nishino, Shinya; Yamamoto, Susumu; Suzuki, Takashi; Ikeda, Minoru; Ohtani, Yasuaki
2018-06-01
A novel tight-binding method is developed, based on the extended Hückel approximation and charge self-consistency, with referring the band structure and the total energy of the local density approximation of the density functional theory. The parameters are so adjusted by computer that the result reproduces the band structure and the total energy, and the algorithm for determining parameters is established. The set of determined parameters is applicable to a variety of crystalline compounds and change of lattice constants, and, in other words, it is transferable. Examples are demonstrated for Si crystals of several crystalline structures varying lattice constants. Since the set of parameters is transferable, the present tight-binding method may be applicable also to molecular dynamics simulations of large-scale systems and long-time dynamical processes.
Kwato-Njock, K
2002-01-01
A search is conducted for the determination of expectation values of r sup q between Dirac and quasirelativistic radial wave functions in the quantum-defect approximation. The phenomenological and supersymmetry-inspired quantum-defect models which have proven so far to yield accurate results are used. The recursive structure of formulae derived on the basis of the hypervirial theorem enables us to develop explicit relations for arbitrary values of q. Detailed numerical calculations concerning alkali-metal-like ions of the Li-, Na- and Cu-iso electronic sequences confirm the superiority of supersymmetry-based quantum-defect theory over quantum-defect orbital and exact orbital quantum number approximations. It is also shown that relativistic rather than quasirelativistic treatment may be used for consistent inclusion of relativistic effects.
Kwato-Njock, M G; Oumarou, B
2002-01-01
A search is conducted for the determination of expectation values of $r^q$ between Dirac and quasirelativistic radial wave functions in the quantum-defect approximation. The phenomenological and supersymmetry-inspired quantum-defect models which have proven so far to yield accurate results are used. The recursive structure of formulae derived on the basis of the hypervirial theorem enables us to develop explicit relations for arbitrary values of $q$. Detailed numerical calculations concerning alkali-metal-like ions of the Li-, Na- and Cu-iso electronic sequences confirm the superiority of supersymmetry-based quantum-defect theory over quantum-defect orbital and exact orbital quantum number approximations. It is also shown that relativistic rather than quasirelativistic treatment may be used for consistent inclusion of relativistic effects.
International Nuclear Information System (INIS)
Ranaivo Nomenjanahary, F.; Rakoto, H.; Ratsimbazafy, J.B.
1994-08-01
This paper is concerned with resistivity sounding measurements performed from single site (vertical sounding) or from several sites (profiles) within a bounded area. The objective is to present an accurate information about the study area and to estimate the likelihood of the produced quantitative models. The achievement of this objective obviously requires quite relevant data and processing methods. It also requires interpretation methods which should take into account the probable effect of an heterogeneous structure. In front of such difficulties, the interpretation of resistivity sounding data inevitably involves the use of inversion methods. We suggest starting the interpretation in simple situation (1-D approximation), and using the rough but correct model obtained as an a-priori model for any more refined interpretation. Related to this point of view, special attention should be paid for the inverse problem applied to the resistivity sounding data. This inverse problem is nonlinear, while linearity inherent in the functional response used to describe the physical experiment. Two different approaches are used to build an approximate but higher dimensional inversion of geoelectrical data: the linear approach and the bayesian statistical approach. Some illustrations of their application in resistivity sounding data acquired at Tritrivakely volcanic lake (single site) and at Mahitsy area (several sites) will be given. (author). 28 refs, 7 figs
Introducing linear functions: an alternative statistical approach
Nolan, Caroline; Herbert, Sandra
2015-12-01
The introduction of linear functions is the turning point where many students decide if mathematics is useful or not. This means the role of parameters and variables in linear functions could be considered to be `threshold concepts'. There is recognition that linear functions can be taught in context through the exploration of linear modelling examples, but this has its limitations. Currently, statistical data is easily attainable, and graphics or computer algebra system (CAS) calculators are common in many classrooms. The use of this technology provides ease of access to different representations of linear functions as well as the ability to fit a least-squares line for real-life data. This means these calculators could support a possible alternative approach to the introduction of linear functions. This study compares the results of an end-of-topic test for two classes of Australian middle secondary students at a regional school to determine if such an alternative approach is feasible. In this study, test questions were grouped by concept and subjected to concept by concept analysis of the means of test results of the two classes. This analysis revealed that the students following the alternative approach demonstrated greater competence with non-standard questions.
CERN. Geneva
2015-01-01
Most physics results at the LHC end in a likelihood ratio test. This includes discovery and exclusion for searches as well as mass, cross-section, and coupling measurements. The use of Machine Learning (multivariate) algorithms in HEP is mainly restricted to searches, which can be reduced to classification between two fixed distributions: signal vs. background. I will show how we can extend the use of ML classifiers to distributions parameterized by physical quantities like masses and couplings as well as nuisance parameters associated to systematic uncertainties. This allows for one to approximate the likelihood ratio while still using a high dimensional feature vector for the data. Both the MEM and ABC approaches mentioned above aim to provide inference on model parameters (like cross-sections, masses, couplings, etc.). ABC is fundamentally tied Bayesian inference and focuses on the “likelihood free” setting where only a simulator is available and one cannot directly compute the likelihood for the dat...
Vega Corona, Antonio; Zárate Banda, Magdalena; Barron Adame, Jose Miguel; Martínez Celorio, René Alfredo; Andina de la Fuente, Diego
2008-01-01
The present study describes the design of an Artificial Neural Network to synthesize the Approximation Function of a Pedometer for the Healthy Life Style Promotion. Experimentally, the approximation function is synthesized using three basic digital pedometers of low cost, these pedometers were calibrated with an advanced pedometer that calculates calories consumed and computes distance travelled with personal stride input. The synthesized approximation function by means of the designed neural...
Wüst, Sabine; Wendt, Verena; Linz, Ricarda; Bittner, Michael
2017-09-01
Cubic splines with equidistant spline sampling points are a common method in atmospheric science, used for the approximation of background conditions by means of filtering superimposed fluctuations from a data series. What is defined as background or superimposed fluctuation depends on the specific research question. The latter also determines whether the spline or the residuals - the subtraction of the spline from the original time series - are further analysed.Based on test data sets, we show that the quality of approximation of the background state does not increase continuously with an increasing number of spline sampling points and/or decreasing distance between two spline sampling points. Splines can generate considerable artificial oscillations in the background and the residuals.We introduce a repeating spline approach which is able to significantly reduce this phenomenon. We apply it not only to the test data but also to TIMED-SABER temperature data and choose the distance between two spline sampling points in a way that is sensitive for a large spectrum of gravity waves.
International Nuclear Information System (INIS)
Kutzler, F.W.; Painter, G.S.
1992-01-01
A fully self-consistent series of nonlocal (gradient) density-functional calculations has been carried out using the augmented-Gaussian-orbital method to determine the magnitude of gradient corrections to the potential-energy curves of the first-row diatomics, Li 2 through F 2 . Both the Langreth-Mehl-Hu and the Perdew-Wang gradient-density functionals were used in calculations of the binding energy, bond length, and vibrational frequency for each dimer. Comparison with results obtained in the local-spin-density approximation (LSDA) using the Vosko-Wilk-Nusair functional, and with experiment, reveals that bond lengths and vibrational frequencies are rather insensitive to details of the gradient functionals, including self-consistency effects, but the gradient corrections reduce the overbinding commonly observed in the LSDA calculations of first-row diatomics (with the exception of Li 2 , the gradient-functional binding-energy error is only 50--12 % of the LSDA error). The improved binding energies result from a large differential energy lowering, which occurs in open-shell atoms relative to the diatomics. The stabilization of the atom arises from the use of nonspherical charge and spin densities in the gradient-functional calculations. This stabilization is negligibly small in LSDA calculations performed with nonspherical densities
Generalized Wigner functions in curved spaces: A new approach
International Nuclear Information System (INIS)
Kandrup, H.E.
1988-01-01
It is well known that, given a quantum field in Minkowski space, one can define Wigner functions f/sub W//sup N/(x 1 ,p 1 ,...,x/sub N/,p/sub N/) which (a) are convenient to analyze since, unlike the field itself, they are c-number quantities and (b) can be interpreted in a limited sense as ''quantum distribution functions.'' Recently, Winter and Calzetta, Habib and Hu have shown one way in which these flat-space Wigner functions can be generalized to a curved-space setting, deriving thereby approximate kinetic equations which make sense ''quasilocally'' for ''short-wavelength modes.'' This paper suggests a completely orthogonal approach for defining curved-space Wigner functions which generalizes instead an object such as the Fourier-transformed f/sub W/ 1 (k,p), which is effectively a two-point function viewed in terms of the ''natural'' creation and annihilation operators a/sup dagger/(p-(12k) and a(p+(12k). The approach suggested here lacks the precise phase-space interpretation implicit in the approach of Winter or Calzetta, Habib, and Hu, but it is useful in that (a) it is geared to handle any ''natural'' mode decomposition, so that (b) it can facilitate exact calculations at least in certain limits, such as for a source-free linear field in a static spacetime
Systemic-Functional Approach to Utilities Supplys
Directory of Open Access Journals (Sweden)
Nikolay I. Komkov
2017-01-01
Full Text Available Purpose: the purpose of the article consists in statement of management approach to development of utilities supply processes based on conflict situations decision – making search. It had appeared in the period of the transition from the planned and directive management to market development. Methods: the research methodology is based on the system analysis of full life cycle processes functioning, forecasting of complex systems development, mathematical modeling of processes of services supply and innovative and investment projects modeling as well as development of supplying services processes. Results: the results of the work are concentrated in the presentation of systemic-functional approach to managing the development of processes of municipal services, able to resolve conflict situations in this sphere. Conclusions and Relevance: the traditional management approach on the basis of elimination of "bottlenecks" and emergencies prevailing within planned and directive system at its transformation in the market conditions has led to accumulation of conflict situations and unsolvable problems. The offered systemic-functional approach based on forecasting of full life cycle of the modernized processes and the services providing systems allows to consider costs of modernization, prime cost and quality of the rendered services.
A functional approach for managing ITER operations
International Nuclear Information System (INIS)
Houtte, Didier van; Sagot, François; Okayama, Katsumi; Blackler, Kenneth
2012-01-01
Highlights: ► A function-oriented approach for defining and organizing all the functions required to perform the mission has been developed. ► A Functional Breakdown Structure providing a complete hierarchy of functions on multiple levels is presented. ► The FBS is used for giving a good visibility of ITER project needs and requirements. ► Reliability (R) and Inherent Availability (A I ) of basic functions are calculated from data on the structures, systems and components (failure rate and time to repair) for obtaining the Availability objectives of the ITER project. - Abstract: ITER is currently the most ambitious project on nuclear fusion research. Its objective is to demonstrate the feasibility of fusion as an energy source for the future. The complexity of the systems required to meet this challenge present many opportunities for omissions or incorrect assumptions. System engineering allows the engineer to deal with such a complexity by developing a Functional Breakdown Structure (FBS). Unlike a Plant Breakdown Structure (PBS), the FBS is a function-oriented tree, not a product-oriented tree. It details operations or activities that have to be performed as needed functions of the architecture, allowing identification of any missing elements, defining the personnel skills required to operate the architecture and managing the machine availability.
Kataev, A. L.; Kazantsev, A. E.; Stepanyantz, K. V.
2018-01-01
We calculate the Adler D-function for N = 1 SQCD in the three-loop approximation using the higher covariant derivative regularization and the NSVZ-like subtraction scheme. The recently formulated all-order relation between the Adler function and the anomalous dimension of the matter superfields defined in terms of the bare coupling constant is first considered and generalized to the case of an arbitrary representation for the chiral matter superfields. The correctness of this all-order relation is explicitly verified at the three-loop level. The special renormalization scheme in which this all-order relation remains valid for the D-function and the anomalous dimension defined in terms of the renormalized coupling constant is constructed in the case of using the higher derivative regularization. The analytic expression for the Adler function for N = 1 SQCD is found in this scheme to the order O (αs2). The problem of scheme-dependence of the D-function and the NSVZ-like equation is briefly discussed.
Directory of Open Access Journals (Sweden)
A.L. Kataev
2018-01-01
Full Text Available We calculate the Adler D-function for N=1 SQCD in the three-loop approximation using the higher covariant derivative regularization and the NSVZ-like subtraction scheme. The recently formulated all-order relation between the Adler function and the anomalous dimension of the matter superfields defined in terms of the bare coupling constant is first considered and generalized to the case of an arbitrary representation for the chiral matter superfields. The correctness of this all-order relation is explicitly verified at the three-loop level. The special renormalization scheme in which this all-order relation remains valid for the D-function and the anomalous dimension defined in terms of the renormalized coupling constant is constructed in the case of using the higher derivative regularization. The analytic expression for the Adler function for N=1 SQCD is found in this scheme to the order O(αs2. The problem of scheme-dependence of the D-function and the NSVZ-like equation is briefly discussed.
Energy Technology Data Exchange (ETDEWEB)
Ribeiro, M., E-mail: ribeiro.jr@oorbit.com.br [Office of Operational Research for Business Intelligence and Technology, Principal Office, Buffalo, Wyoming 82834 (United States)
2015-06-21
Ab initio calculations of hydrogen-passivated Si nanowires were performed using density functional theory within LDA-1/2, to account for the excited states properties. A range of diameters was calculated to draw conclusions about the ability of the method to correctly describe the main trends of bandgap, quantum confinement, and self-energy corrections versus the diameter of the nanowire. Bandgaps are predicted with excellent accuracy if compared with other theoretical results like GW, and with the experiment as well, but with a low computational cost.
International Nuclear Information System (INIS)
Ribeiro, M.
2015-01-01
Ab initio calculations of hydrogen-passivated Si nanowires were performed using density functional theory within LDA-1/2, to account for the excited states properties. A range of diameters was calculated to draw conclusions about the ability of the method to correctly describe the main trends of bandgap, quantum confinement, and self-energy corrections versus the diameter of the nanowire. Bandgaps are predicted with excellent accuracy if compared with other theoretical results like GW, and with the experiment as well, but with a low computational cost
Choi, Ji Yeh; Hwang, Heungsun; Yamamoto, Michio; Jung, Kwanghee; Woodward, Todd S
2017-06-01
Functional principal component analysis (FPCA) and functional multiple-set canonical correlation analysis (FMCCA) are data reduction techniques for functional data that are collected in the form of smooth curves or functions over a continuum such as time or space. In FPCA, low-dimensional components are extracted from a single functional dataset such that they explain the most variance of the dataset, whereas in FMCCA, low-dimensional components are obtained from each of multiple functional datasets in such a way that the associations among the components are maximized across the different sets. In this paper, we propose a unified approach to FPCA and FMCCA. The proposed approach subsumes both techniques as special cases. Furthermore, it permits a compromise between the techniques, such that components are obtained from each set of functional data to maximize their associations across different datasets, while accounting for the variance of the data well. We propose a single optimization criterion for the proposed approach, and develop an alternating regularized least squares algorithm to minimize the criterion in combination with basis function approximations to functions. We conduct a simulation study to investigate the performance of the proposed approach based on synthetic data. We also apply the approach for the analysis of multiple-subject functional magnetic resonance imaging data to obtain low-dimensional components of blood-oxygen level-dependent signal changes of the brain over time, which are highly correlated across the subjects as well as representative of the data. The extracted components are used to identify networks of neural activity that are commonly activated across the subjects while carrying out a working memory task.
Directory of Open Access Journals (Sweden)
Zanzi Luigi
2010-01-01
Full Text Available The two-step approach is a fast algorithm for 3D migration originally introduced to process zero-offset seismic data. Its application to monostatic GPR (Ground Penetrating Radar data is straightforward. A direct extension of the algorithm for the application to bistatic radar data is possible provided that the TX-RX azimuth is constant. As for the zero-offset case, the two-step operator is exactly equivalent to the one-step 3D operator for a constant velocity medium and is an approximation of the one-step 3D operator for a medium where the velocity varies vertically. Two methods are explored for handling a heterogeneous medium; both are suitable for the application of the two-step approach, and they are compared in terms of accuracy of the final 3D operator. The aperture of the two-step operator is discussed, and a solution is proposed to optimize its shape. The analysis is of interest for any NDT application where the medium is expected to be heterogeneous, or where the antenna is not in direct contact with the medium (e.g., NDT of artworks, humanitarian demining, radar with air-launched antennas.
International Nuclear Information System (INIS)
Kocifaj, Miroslav
2016-01-01
The study of diffuse light of a night sky is undergoing a renaissance due to the development of inexpensive high performance computers which can significantly reduce the time needed for accurate numerical simulations. Apart from targeted field campaigns, numerical modeling appears to be one of the most attractive and powerful approaches for predicting the diffuse light of a night sky. However, computer-aided simulation of night-sky radiances over any territory and under arbitrary conditions is a complex problem that is difficult to solve. This study addresses three concepts for modeling the artificial light propagation through a turbid stratified atmosphere. Specifically, these are two-stream approximation, iterative approach to Radiative Transfer Equation (RTE) and Method of Successive Orders of Scattering (MSOS). The principles of the methods, their strengths and weaknesses are reviewed with respect to their implications for night-light modeling in different environments. - Highlights: • Three methods for modeling nightsky radiance are reviewed. • The two-stream approximation allows for rapid calculation of radiative fluxes. • The above approach is convenient for modeling large uniformly emitting areas. • SOS is applicable to heterogeneous deployment of well-separated cities or towns. • MSOS is generally CPU less-intensive than traditional 3D RTE.
Estimating Function Approaches for Spatial Point Processes
Deng, Chong
Spatial point pattern data consist of locations of events that are often of interest in biological and ecological studies. Such data are commonly viewed as a realization from a stochastic process called spatial point process. To fit a parametric spatial point process model to such data, likelihood-based methods have been widely studied. However, while maximum likelihood estimation is often too computationally intensive for Cox and cluster processes, pairwise likelihood methods such as composite likelihood, Palm likelihood usually suffer from the loss of information due to the ignorance of correlation among pairs. For many types of correlated data other than spatial point processes, when likelihood-based approaches are not desirable, estimating functions have been widely used for model fitting. In this dissertation, we explore the estimating function approaches for fitting spatial point process models. These approaches, which are based on the asymptotic optimal estimating function theories, can be used to incorporate the correlation among data and yield more efficient estimators. We conducted a series of studies to demonstrate that these estmating function approaches are good alternatives to balance the trade-off between computation complexity and estimating efficiency. First, we propose a new estimating procedure that improves the efficiency of pairwise composite likelihood method in estimating clustering parameters. Our approach combines estimating functions derived from pairwise composite likeli-hood estimation and estimating functions that account for correlations among the pairwise contributions. Our method can be used to fit a variety of parametric spatial point process models and can yield more efficient estimators for the clustering parameters than pairwise composite likelihood estimation. We demonstrate its efficacy through a simulation study and an application to the longleaf pine data. Second, we further explore the quasi-likelihood approach on fitting
Approximate Implicitization Using Linear Algebra
Directory of Open Access Journals (Sweden)
Oliver J. D. Barrowclough
2012-01-01
Full Text Available We consider a family of algorithms for approximate implicitization of rational parametric curves and surfaces. The main approximation tool in all of the approaches is the singular value decomposition, and they are therefore well suited to floating-point implementation in computer-aided geometric design (CAGD systems. We unify the approaches under the names of commonly known polynomial basis functions and consider various theoretical and practical aspects of the algorithms. We offer new methods for a least squares approach to approximate implicitization using orthogonal polynomials, which tend to be faster and more numerically stable than some existing algorithms. We propose several simple propositions relating the properties of the polynomial bases to their implicit approximation properties.
Directory of Open Access Journals (Sweden)
Simon Boitard
2016-03-01
Full Text Available Inferring the ancestral dynamics of effective population size is a long-standing question in population genetics, which can now be tackled much more accurately thanks to the massive genomic data available in many species. Several promising methods that take advantage of whole-genome sequences have been recently developed in this context. However, they can only be applied to rather small samples, which limits their ability to estimate recent population size history. Besides, they can be very sensitive to sequencing or phasing errors. Here we introduce a new approximate Bayesian computation approach named PopSizeABC that allows estimating the evolution of the effective population size through time, using a large sample of complete genomes. This sample is summarized using the folded allele frequency spectrum and the average zygotic linkage disequilibrium at different bins of physical distance, two classes of statistics that are widely used in population genetics and can be easily computed from unphased and unpolarized SNP data. Our approach provides accurate estimations of past population sizes, from the very first generations before present back to the expected time to the most recent common ancestor of the sample, as shown by simulations under a wide range of demographic scenarios. When applied to samples of 15 or 25 complete genomes in four cattle breeds (Angus, Fleckvieh, Holstein and Jersey, PopSizeABC revealed a series of population declines, related to historical events such as domestication or modern breed creation. We further highlight that our approach is robust to sequencing errors, provided summary statistics are computed from SNPs with common alleles.
Green functions of graphene: An analytic approach
Energy Technology Data Exchange (ETDEWEB)
Lawlor, James A., E-mail: jalawlor@tcd.ie [School of Physics, Trinity College Dublin, Dublin 2 (Ireland); Ferreira, Mauro S. [School of Physics, Trinity College Dublin, Dublin 2 (Ireland); CRANN, Trinity College Dublin, Dublin 2 (Ireland)
2015-04-15
In this article we derive the lattice Green Functions (GFs) of graphene using a Tight Binding Hamiltonian incorporating both first and second nearest neighbour hoppings and allowing for a non-orthogonal electron wavefunction overlap. It is shown how the resulting GFs can be simplified from a double to a single integral form to aid computation, and that when considering off-diagonal GFs in the high symmetry directions of the lattice this single integral can be approximated very accurately by an algebraic expression. By comparing our results to the conventional first nearest neighbour model commonly found in the literature, it is apparent that the extended model leads to a sizeable change in the electronic structure away from the linear regime. As such, this article serves as a blueprint for researchers who wish to examine quantities where these considerations are important.
Rational approximation of vertical segments
Salazar Celis, Oliver; Cuyt, Annie; Verdonk, Brigitte
2007-08-01
In many applications, observations are prone to imprecise measurements. When constructing a model based on such data, an approximation rather than an interpolation approach is needed. Very often a least squares approximation is used. Here we follow a different approach. A natural way for dealing with uncertainty in the data is by means of an uncertainty interval. We assume that the uncertainty in the independent variables is negligible and that for each observation an uncertainty interval can be given which contains the (unknown) exact value. To approximate such data we look for functions which intersect all uncertainty intervals. In the past this problem has been studied for polynomials, or more generally for functions which are linear in the unknown coefficients. Here we study the problem for a particular class of functions which are nonlinear in the unknown coefficients, namely rational functions. We show how to reduce the problem to a quadratic programming problem with a strictly convex objective function, yielding a unique rational function which intersects all uncertainty intervals and satisfies some additional properties. Compared to rational least squares approximation which reduces to a nonlinear optimization problem where the objective function may have many local minima, this makes the new approach attractive.
Bureick, Johannes; Alkhatib, Hamza; Neumann, Ingo
2016-03-01
In many geodetic engineering applications it is necessary to solve the problem of describing a measured data point cloud, measured, e. g. by laser scanner, by means of free-form curves or surfaces, e. g., with B-Splines as basis functions. The state of the art approaches to determine B-Splines yields results which are seriously manipulated by the occurrence of data gaps and outliers. Optimal and robust B-Spline fitting depend, however, on optimal selection of the knot vector. Hence we combine in our approach Monte-Carlo methods and the location and curvature of the measured data in order to determine the knot vector of the B-Spline in such a way that no oscillating effects at the edges of data gaps occur. We introduce an optimized approach based on computed weights by means of resampling techniques. In order to minimize the effect of outliers, we apply robust M-estimators for the estimation of control points. The above mentioned approach will be applied to a multi-sensor system based on kinematic terrestrial laserscanning in the field of rail track inspection.
Hanson-Heine, Magnus W. D.; George, Michael W.; Besley, Nicholas A.
2018-06-01
The restricted excitation subspace approximation is explored as a basis to reduce the memory storage required in linear response time-dependent density functional theory (TDDFT) calculations within the Tamm-Dancoff approximation. It is shown that excluding the core orbitals and up to 70% of the virtual orbitals in the construction of the excitation subspace does not result in significant changes in computed UV/vis spectra for large molecules. The reduced size of the excitation subspace greatly reduces the size of the subspace vectors that need to be stored when using the Davidson procedure to determine the eigenvalues of the TDDFT equations. Furthermore, additional screening of the two-electron integrals in combination with a reduction in the size of the numerical integration grid used in the TDDFT calculation leads to significant computational savings. The use of these approximations represents a simple approach to extend TDDFT to the study of large systems and make the calculations increasingly tractable using modest computing resources.
Directory of Open Access Journals (Sweden)
HU Qi-guo
2017-01-01
Full Text Available For reducing the vehicle compartment low frequency noise, the Optimal Latin hypercube sampling method was applied to perform experimental design for sampling in the factorial design space. The thickness parameters of the panels with larger acoustic contribution was considered as factors, as well as the vehicle mass, seventh rank modal frequency of body, peak sound pressure of test point and sound pressure root-mean-square value as responses. By using the RBF(radial basis function neuro-network method, an approximation model of four responses about six factors was established. Further more, error analysis of established approximation model was performed in this paper. To optimize the panel’s thickness parameter, the adaptive simulated annealing algorithm was im-plemented. Optimization results show that the peak sound pressure of driver’s head was reduced by 4.45dB and 5.47dB at frequency 158HZ and 134Hz respec-tively. The test point pressure were significantly reduced at other frequency as well. The results indicate that through the optimization the vehicle interior cavity noise was reduced effectively, and the acoustical comfort of the vehicle was im-proved significantly.
A density functional approach to ferrogels
Cremer, P.; Heinen, M.; Menzel, A. M.; Löwen, H.
2017-07-01
Ferrogels consist of magnetic colloidal particles embedded in an elastic polymer matrix. As a consequence, their structural and rheological properties are governed by a competition between magnetic particle-particle interactions and mechanical matrix elasticity. Typically, the particles are permanently fixed within the matrix, which makes them distinguishable by their positions. Over time, particle neighbors do not change due to the fixation by the matrix. Here we present a classical density functional approach for such ferrogels. We map the elastic matrix-induced interactions between neighboring colloidal particles distinguishable by their positions onto effective pairwise interactions between indistinguishable particles similar to a ‘pairwise pseudopotential’. Using Monte-Carlo computer simulations, we demonstrate for one-dimensional dipole-spring models of ferrogels that this mapping is justified. We then use the pseudopotential as an input into classical density functional theory of inhomogeneous fluids and predict the bulk elastic modulus of the ferrogel under various conditions. In addition, we propose the use of an ‘external pseudopotential’ when one switches from the viewpoint of a one-dimensional dipole-spring object to a one-dimensional chain embedded in an infinitely extended bulk matrix. Our mapping approach paves the way to describe various inhomogeneous situations of ferrogels using classical density functional concepts of inhomogeneous fluids.
Rao, D. V.; Takeda, T.; Itai, Y.; Akatsuka, T.; Seltzer, S. M.; Hubbell, J. H.; Cesareo, R.; Brunetti, A.; Gigante, G. E.
Atomic Rayleigh scattering cross-sections for low, medium and high Z atoms are measured in vacuum using X-ray tube with a secondary target as an excitation source instead of radioisotopes. Monoenergetic Kα radiation emitted from the secondary target and monoenergetic radiation produced using two secondary targets with filters coupled to an X-ray tube are compared. The Kα radiation from the second target of the system is used to excite the sample. The background has been reduced considerably and the monochromacy is improved. Elastic scattering of Kα X-ray line energies of the secondary target by the sample is recorded with Hp Ge and Si (Li) detectors. A new approach is developed to estimate the solid angle approximation and geometrical efficiency for a system with experimental arrangement using X-ray tube and secondary target. The variation of the solid angle is studied by changing the radius and length of the collimators towards and away from the source and sample. From these values the variation of the total solid angle and geometrical efficiency is deduced and the optimum value is used for the experimental work. The efficiency is larger because the X-ray fluorescent source acts as a converter. Experimental results based on this system are compared with theoretical estimates and good agreement is observed in between them.
International Nuclear Information System (INIS)
Denner, A.; Dittmaier, S.; Roth, M.; Wackeroth, D.
2000-01-01
We calculate the complete O(α) electroweak radiative corrections to e + e - →WW→4f in the electroweak Standard Model in the double-pole approximation. We give analytical results for the non-factorizable virtual corrections and express the factorizable virtual corrections in terms of the known corrections to on-shell W-pair production and W decay. The calculation of the bremsstrahlung corrections, i.e., the processes e + e - →4fγ in lowest order, is based on the full matrix elements. The matching of soft and collinear singularities between virtual and real corrections is done alternatively in two different ways, namely by using a subtraction method and by applying phase-space slicing. The O(α) corrections as well as higher-order initial-state photon radiation are implemented in the Monte Carlo generator RACOONWW. Numerical results of this program are presented for the W-pair-production cross section, angular and W-invariant-mass distributions at LEP2. We also discuss the intrinsic theoretical uncertainty of our approach
Functional approximations to posterior densities: a neural network approach to efficient sampling
L.F. Hoogerheide (Lennart); J.F. Kaashoek (Johan); H.K. van Dijk (Herman)
2002-01-01
textabstractThe performance of Monte Carlo integration methods like importance sampling or Markov Chain Monte Carlo procedures greatly depends on the choice of the importance or candidate density. Usually, such a density has to be "close" to the target density in order to yield numerically accurate
International Nuclear Information System (INIS)
Ginsburg, C.A.
1980-01-01
In many problems, a desired property A of a function f(x) is determined by the behaviour of f(x) approximately equal to g(x,A) as x→xsup(*). In this letter, a method for resuming the power series in x of f(x) and approximating A (modulated Pade approximant) is presented. This new approximant is an extension of a resumation method for f(x) in terms of rational functions. (author)
Radiological emergency response - a functional approach
Energy Technology Data Exchange (ETDEWEB)
Chowdhury, Prosanta [Louisiana Radiation Protection Div., Baton Rouge, LA (United States)
1997-12-31
The radiological emergency response program in the State of Louisiana is discussed. The improved approach intends to maximize the efficiency for both nuclear power plant and radiological emergency response as a whole. Several broad-based components are identified: cluster of `nodes` are generated for each component; these `nodes` may be divided into `sub-nodes` which will contain some `attributes`; `relational bonds` among the `attributes` will exist. When executed, the process begins and continues with the `nodes` assuming a functional and dynamic role based on the nature and characteristics of the `attributes`. The typical response based on stand-alone elements is eliminated; overlapping of functions is avoided, and is produced a well-structure and efficient organization 1 ref., 6 figs.; e-mail: prosanta at deq.state.la.us
Radiological emergency response - a functional approach
International Nuclear Information System (INIS)
Chowdhury, Prosanta
1997-01-01
The radiological emergency response program in the State of Louisiana is discussed. The improved approach intends to maximize the efficiency for both nuclear power plant and radiological emergency response as a whole. Several broad-based components are identified: cluster of 'nodes' are generated for each component; these 'nodes' may be divided into 'sub-nodes' which will contain some 'attributes'; 'relational bonds' among the 'attributes' will exist. When executed, the process begins and continues with the 'nodes' assuming a functional and dynamic role based on the nature and characteristics of the 'attributes'. The typical response based on stand-alone elements is eliminated; overlapping of functions is avoided, and is produced a well-structure and efficient organization
Functional genomics approaches in parasitic helminths.
Hagen, J; Lee, E F; Fairlie, W D; Kalinna, B H
2012-01-01
As research on parasitic helminths is moving into the post-genomic era, an enormous effort is directed towards deciphering gene function and to achieve gene annotation. The sequences that are available in public databases undoubtedly hold information that can be utilized for new interventions and control but the exploitation of these resources has until recently remained difficult. Only now, with the emergence of methods to genetically manipulate and transform parasitic worms will it be possible to gain a comprehensive understanding of the molecular mechanisms involved in nutrition, metabolism, developmental switches/maturation and interaction with the host immune system. This review focuses on functional genomics approaches in parasitic helminths that are currently used, to highlight potential applications of these technologies in the areas of cell biology, systems biology and immunobiology of parasitic helminths. © 2011 Blackwell Publishing Ltd.
An improved saddlepoint approximation.
Gillespie, Colin S; Renshaw, Eric
2007-08-01
Given a set of third- or higher-order moments, not only is the saddlepoint approximation the only realistic 'family-free' technique available for constructing an associated probability distribution, but it is 'optimal' in the sense that it is based on the highly efficient numerical method of steepest descents. However, it suffers from the problem of not always yielding full support, and whilst [S. Wang, General saddlepoint approximations in the bootstrap, Prob. Stat. Lett. 27 (1992) 61.] neat scaling approach provides a solution to this hurdle, it leads to potentially inaccurate and aberrant results. We therefore propose several new ways of surmounting such difficulties, including: extending the inversion of the cumulant generating function to second-order; selecting an appropriate probability structure for higher-order cumulants (the standard moment closure procedure takes them to be zero); and, making subtle changes to the target cumulants and then optimising via the simplex algorithm.
Energy Technology Data Exchange (ETDEWEB)
Sato, Shunsuke A. [Graduate School of Pure and Applied Sciences, University of Tsukuba, Tsukuba 305-8571 (Japan); Taniguchi, Yasutaka [Center for Computational Science, University of Tsukuba, Tsukuba 305-8571 (Japan); Department of Medical and General Sciences, Nihon Institute of Medical Science, 1276 Shimogawara, Moroyama-Machi, Iruma-Gun, Saitama 350-0435 (Japan); Shinohara, Yasushi [Max Planck Institute of Microstructure Physics, 06120 Halle (Germany); Yabana, Kazuhiro [Graduate School of Pure and Applied Sciences, University of Tsukuba, Tsukuba 305-8571 (Japan); Center for Computational Science, University of Tsukuba, Tsukuba 305-8571 (Japan)
2015-12-14
We develop methods to calculate electron dynamics in crystalline solids in real-time time-dependent density functional theory employing exchange-correlation potentials which reproduce band gap energies of dielectrics; a meta-generalized gradient approximation was proposed by Tran and Blaha [Phys. Rev. Lett. 102, 226401 (2009)] (TBm-BJ) and a hybrid functional was proposed by Heyd, Scuseria, and Ernzerhof [J. Chem. Phys. 118, 8207 (2003)] (HSE). In time evolution calculations employing the TB-mBJ potential, we have found it necessary to adopt the predictor-corrector step for a stable time evolution. We have developed a method to evaluate electronic excitation energy without referring to the energy functional which is unknown for the TB-mBJ potential. For the HSE functional, we have developed a method for the operation of the Fock-like term in Fourier space to facilitate efficient use of massive parallel computers equipped with graphic processing units. We compare electronic excitations in silicon and germanium induced by femtosecond laser pulses using the TB-mBJ, HSE, and a simple local density approximation (LDA). At low laser intensities, electronic excitations are found to be sensitive to the band gap energy: they are close to each other using TB-mBJ and HSE and are much smaller in LDA. At high laser intensities close to the damage threshold, electronic excitation energies do not differ much among the three cases.
Value Function Approximation or Stopping Time Approximation
DEFF Research Database (Denmark)
Stentoft, Lars
2014-01-01
In their 2001 paper, Longstaff and Schwartz suggested a method for American option pricing using simulation and regression, and since then this method has rapidly gained importance. However, the idea of using regression and simulation for American option pricing was used at least as early as 1996......, due to this difference, it is possible to provide arguments favoring the method of Longstaff and Schwartz. Finally, we compare the methods in a realistic numerical setting and show that practitioners would do well to choose the method of Longstaff and Schwartz instead of the methods of Carriere...
International Nuclear Information System (INIS)
Bricka, M.
1962-03-01
This report addresses the problem of determination of neutron spectrum by using a set of detectors. The spectrum approximation method based on a polygonal function is more particularly studied. The author shows that the coefficients of the usual mathematical model can be simply formulated and assessed. The study of spectra approximation by a polygonal function shows that dose can be expressed by a linear function of the activity of the different detectors [fr
International Nuclear Information System (INIS)
Kulakovskij, M.Ya.; Savitskij, V.I.
1981-01-01
The errors of multigroup calculating the neutron flux spatial and energy distribution in the fast reactor shield caused by using group and age approximations are considered. It is shown that at small distances from a source the age theory rather well describes the distribution of the slowing-down density. With the distance increase the age approximation leads to underestimating the neutron fluxes, and the error quickly increases at that. At small distances from the source (up to 15 lengths of free path in graphite) the multigroup diffusion approximation describes the distribution of slowing down density quite satisfactorily and at that the results almost do not depend on the number of groups. With the distance increase the multigroup diffusion calculations lead to considerable overestimating of the slowing-down density. The conclusion is drawn that the group approximation proper errors are opposite in sign to the error introduced by the age approximation and to some extent compensate each other
A new approach to evaluate the response functions for conical and cylindrical collimators
International Nuclear Information System (INIS)
Gigante, G.E.
1989-01-01
A new approach to the evaluation of the conical collimator response function is shown. The basic collimator formulae are reviewed. The collimator response function has been found in a very easy way. An approximate solution has been introduced. Studying the response of a measuring system, the use of this approximation strongly reduces the complexity of the relations to be used; therefore it would provide a useful starting point for a Monte Carlo calculation. The errors introduced are less than 10%. Approximate relations that allow the evaluation of the response of conical and cylindrical collimators to plane and line sources are also given. (orig.)
Radiological emergency response - a functional approach
International Nuclear Information System (INIS)
Chowdhury, P.
1998-01-01
The state of Louisiana's radiological emergency response programme is based on the federal guidance 'Criteria for Preparation and Evaluation of Radiological Emergency Response Plans and Preparedness in Support of Nuclear Power Plants' (NUREG-0654, FEMA-REP-1 Rev. 1). Over the past 14 years, the planning and implementation of response capabilities became more organized and efficient; the training programme has strengthened considerably; co-ordination with all participating agencies has assumed a more co-operative role, and as a result, a fairly well integrated response planning has evolved. Recently, a more 'functional' approach is being adopted to maximize the programme's efficiency not only for nuclear power plant emergency response, but radiological emergency response as a whole. First, several broad-based 'components' are identified; clusters of 'nodes' are generated for each component; these 'nodes' may be divided into 'sub-nodes' which will contain some 'attributes'; 'relational bonds' among the 'attributes' will exist. When executed, the process begins and continues with the 'nodes' assuming a functional and dynamic role based on the nature and characteristics of the 'attributes'. The typical response based on stand-alone elements is thus eliminated, the overlapping of functions is avoided, and a well structured and efficient organization is produced, that is essential for today's complex nature of emergency response. (author)
Approach to ''Mind'' using functional neuroimaging
International Nuclear Information System (INIS)
Matsuda, Hiroshi
2006-01-01
This review mainly describes authors' recent investigations concerning neuroimages approaching to even human ''mind'' using techniques of PET, SPECT and functional MRI (fMRI). Progress of such studies greatly owes to the development of image statistics of the brain like statistical parametric mapping (www.fil.ion.ucl.ac.uk/spm/), and brain standards (www.mrc-cbu.cam.ac.uk/Imaging/mnispace.html, and ric.uthscsa.edu/projects/talairach daemon.html). The author discusses and presents images in cases of hallucinations (SPECT and H 2 15 O-PET), autism (SPECT), sleep, depression, and its therapy by transcaranial magnetic stimulation. These studies are expected to contribute to diagnosis and therapy of endogenous neurological disorders. (T.I.)
Approach to ''Mind'' using functional neuroimaging
Energy Technology Data Exchange (ETDEWEB)
Matsuda, Hiroshi [Saitama Medical School, Hospital, Moroyama, Saitama (Japan)
2006-05-15
This review mainly describes authors' recent investigations concerning neuroimages approaching to even human ''mind'' using techniques of PET, SPECT and functional MRI (fMRI). Progress of such studies greatly owes to the development of image statistics of the brain like statistical parametric mapping (www.fil.ion.ucl.ac.uk/spm/), and brain standards (www.mrc-cbu.cam.ac.uk/Imaging/mnispace.html, and ric.uthscsa.edu/projects/talairach daemon.html). The author discusses and presents images in cases of hallucinations (SPECT and H{sub 2}{sup 15}O-PET), autism (SPECT), sleep, depression, and its therapy by transcaranial magnetic stimulation. These studies are expected to contribute to diagnosis and therapy of endogenous neurological disorders. (T.I.)
Quantum anharmonic oscillator: The airy function approach
Energy Technology Data Exchange (ETDEWEB)
Maiz, F., E-mail: fethimaiz@gmail.com [King Khalid University, Faculty of Science, Physics Department, PO Box 9004, Abha 61413, Asseer (Saudi Arabia); University of Cartage, Nabeul Engineering Preparatory Institute, Merazka, 8000 Nabeul (Tunisia); AlFaify, S. [King Khalid University, Faculty of Science, Physics Department, PO Box 9004, Abha 61413, Asseer (Saudi Arabia)
2014-05-15
New and simple numerical method is being reported to solve anharmonic oscillator problems. The method is setup to approach the real potential V(x) of the anharmonic oscillator system as a piecewise linear potential u(x) and to solve the Schrödinger equation of the system using the Airy function. Then, solutions continuity conditions lead to the energy quantification condition, and consequently, the energy eigenvalues. For testing purpose, the method was applied on the sextic and octic oscillators systems. The proposed method is found to be realistic, computationally simple, and having high degrees of accuracy. In addition, it can be applied to any form of potential. The results obtained by the proposed method were seen closely agreeing with results reached by other complicated methods.
Eikonal Approximation in AdS/CFT: Conformal Partial Waves and Finite N Four-Point Functions
Cornalba, L; Penedones, J; Schiappa, R; Cornalba, Lorenzo; Costa, Miguel S.; Penedones, Joao; Schiappa, Ricardo
2007-01-01
We introduce the impact-parameter representation for conformal field theory correlators of the form A ~ . This representation is appropriate in the eikonal kinematical regime, and approximates the conformal partial-wave decomposition in the limit of large spin and dimension of the exchanged primary. Using recent results on the two-point function _{shock} in the presence of a shock wave in Anti-de Sitter, and its relation to the discontinuity of the four-point amplitude A across a kinematical branch-cut, we find the high spin and dimension conformal partial- wave decomposition of all tree-level Anti-de Sitter Witten diagrams. We show that, as in flat space, the eikonal kinematical regime is dominated by the T-channel exchange of the massless particle with highest spin (graviton dominance). We also compute the anomalous dimensions of the high-spin O_1 O_2 composites. Finally, we conjecture a formula re-summing crossed-ladder Witten diagrams to all orders in the gravitational coupling.
Eikonal approximation in AdS/CFT: Conformal partial waves and finite N four-point functions
International Nuclear Information System (INIS)
Cornalba, Lorenzo; Costa, Miguel S.; Penedones, Joao; Schiappa, Ricardo
2007-01-01
We introduce the impact parameter representation for conformal field theory correlators of the form A∼ 1 O 2 O 1 O 2 >. This representation is appropriate in the eikonal kinematical regime, and approximates the conformal partial wave decomposition in the limit of large spin and dimension of the exchanged primary. Using recent results on the two-point function 1 O 1 > shock in the presence of a shock wave in anti-de Sitter, and its relation to the discontinuity of the four-point amplitude A across a kinematical branch cut, we find the high spin and dimension conformal partial wave decomposition of all tree-level anti-de Sitter Witten diagrams. We show that, as in flat space, the eikonal kinematical regime is dominated by the T-channel exchange of the massless particle with highest spin (graviton dominance). We also compute the anomalous dimensions of the high spin O 1 O 2 composites. Finally, we conjecture a formula re-summing crossed-ladder Witten diagrams to all orders in the gravitational coupling
International Nuclear Information System (INIS)
Pollock, M.D.
1988-01-01
In quantum cosmology, a wave function Ψ for a given theory can be obtained by solving the Wheeler-DeWitt equation, using the semi-classical approximation to the path integral over euclidean metrics to impose the boundary condition, as described by Hawking and his collaborators. If the universe is expanding as a quasi-de Sitter space-time, then it is possible to derive a Fokker-Planck equation for the probability distribution P, as shown by Starobinsky. Arguing by analogy with quantum mechanics in flat space-time, one would expect that P ∝ ΨΨ * . We examine this assertion by reference to the scale-invariant theory L = -1/24 βR 2 , whose wave function has been calculated in mini-superspace by Horowitz, and whose classical solutions are de Sitter space-times. It appears that deviations from the relation P ∝ ΨΨ * are attributable to long-wavelength fluctuations δΦ e ≅ H/2π in the effective inflaton field Φ c =√(βR)=√(12β) H. Their existence is taken into account in the derivation of the Fokker-Planck equation, but not in the derivation of Ψ when this is restricted to mini-superspace. In the limit β → ∞, we find that δΦ e /Φ c → 0 and that P ∝ ΨΨ * . The scale-invariant theory L = (1/2εφ 2 R-1/4λΦ 4 ) can be similarly analyzed. Inclusion of a kinetic term 1/2Φ; k Φ ;k destroys this similarity, which is restored however upon addition of a term (-1/24βR 2 ). (orig.)
Directory of Open Access Journals (Sweden)
H. K. Hetman
2011-01-01
Full Text Available A number of functions for approximating the universal magnetic curve and its derivatives, their accuracy and conformity to the requirements put forward by the authors have been studied.
``Green's function'' approach & low-mode asymmetries
Masse, Laurent; Clark, Dan; Salmonson, Jay; MacLaren, Steve; Ma, Tammy; Khan, Shahab; Pino, Jesse; Ralph, Jo; Czajka, C.; Tipton, Robert; Landen, Otto; Kyrala, Georges; 2 Team; 1 Team
2017-10-01
Long wavelength, low mode asymmetries are believed to play a leading role in limiting the performance of current ICF implosions on NIF. These long wavelength modes are initiated and driven by asymmetries in the x-ray flux from the hohlraum; however, the underlying hydrodynamics of the implosion also act to amplify these asymmetries. The work presented here aim to deepen our understanding of the interplay of the drive asymmetries and the underlying implosion hydrodynamics in determining the final imploded configuration. This is accomplished through a synthesis of numerical modeling, analytic theory, and experimental data. In detail, we use a Green's function approach to connect the drive asymmetry seen by the capsule to the measured inflight and hot spot symmetries. The approach has been validated against a suite of numerical simulations. Ultimately, we hope this work will identify additional measurements to further constrain the asymmetries and increase hohlraum illumination design flexibility on the NIF. The technique and derivation of associated error bars will be presented. LLC, (LLNS) Contract No. DE-AC52-07NA27344.
Dagrau, Franck; Coulouvrat, François; Marchiano, Régis; Héron, Nicolas
2008-06-01
Dassault Aviation as a civil aircraft manufacturer is studying the feasibility of a supersonic business jet with the target of an "acceptable" sonic boom at the ground level, and in particular in case of focusing. A sonic boom computational process has been performed, that takes into account meteorological effects and aircraft manoeuvres. Turn manoeuvres and aircraft acceleration create zones of convergence of rays (caustics) which are the place of sound amplification. Therefore two elements have to be evaluated: firstly the geometrical position of the caustics, and secondly the noise level in the neighbourhood of the caustics. The modelling of the sonic boom propagation is based essentially on the assumptions of geometrical acoustics. Ray tracing is obtained according to Fermat's principle as paths that minimise the propagation time between the source (the aircraft) and the receiver. Wave amplitude and time waveform result from the solution of the inviscid Burgers' equation written along each individual ray. The "age variable" measuring the cumulative nonlinear effects is linked to the ray tube area. Caustics are located as the place where the ray tube area vanishes. Since geometrical acoustics does not take into account diffraction effects, it breaks down in the neighbourhood of caustics where it would predict unphysical infinite pressure amplitude. The aim of this study is to describe an original method for computing the focused noise level. The approach involves three main steps that can be summarised as follows. The propagation equation is solved by a forward marching procedure split into three successive steps: linear propagation in a homogeneous medium, linear perturbation due to the weak heterogeneity of the medium, and non-linear effects. The first step is solved using an "exact" angular spectrum algorithm. Parabolic approximation is applied only for the weak perturbation due to the heterogeneities. Finally, non linear effects are performed by solving the
Tutu, Hiroki
2011-06-01
Stochastic resonance (SR) enhanced by time-delayed feedback control is studied. The system in the absence of control is described by a Langevin equation for a bistable system, and possesses a usual SR response. The control with the feedback loop, the delay time of which equals to one-half of the period (2π/Ω) of the input signal, gives rise to a noise-induced oscillatory switching cycle between two states in the output time series, while its average frequency is just smaller than Ω in a small noise regime. As the noise intensity D approaches an appropriate level, the noise constructively works to adapt the frequency of the switching cycle to Ω, and this changes the dynamics into a state wherein the phase of the output signal is entrained to that of the input signal from its phase slipped state. The behavior is characterized by power loss of the external signal or response function. This paper deals with the response function based on a dichotomic model. A method of delay-coordinate series expansion, which reduces a non-Markovian transition probability flux to a series of memory fluxes on a discrete delay-coordinate system, is proposed. Its primitive implementation suggests that the method can be a potential tool for a systematic analysis of SR phenomenon with delayed feedback loop. We show that a D-dependent behavior of poles of a finite Laplace transform of the response function qualitatively characterizes the structure of the power loss, and we also show analytical results for the correlation function and the power spectral density.
Approximations of Fuzzy Systems
Directory of Open Access Journals (Sweden)
Vinai K. Singh
2013-03-01
Full Text Available A fuzzy system can uniformly approximate any real continuous function on a compact domain to any degree of accuracy. Such results can be viewed as an existence of optimal fuzzy systems. Li-Xin Wang discussed a similar problem using Gaussian membership function and Stone-Weierstrass Theorem. He established that fuzzy systems, with product inference, centroid defuzzification and Gaussian functions are capable of approximating any real continuous function on a compact set to arbitrary accuracy. In this paper we study a similar approximation problem by using exponential membership functions
CONTRIBUTIONS TO RATIONAL APPROXIMATION,
Some of the key results of linear Chebyshev approximation theory are extended to generalized rational functions. Prominent among these is Haar’s...linear theorem which yields necessary and sufficient conditions for uniqueness. Some new results in the classic field of rational function Chebyshev...Furthermore a Weierstrass type theorem is proven for rational Chebyshev approximation. A characterization theorem for rational trigonometric Chebyshev approximation in terms of sign alternation is developed. (Author)
International Nuclear Information System (INIS)
De Backer, A; Sand, A; Ortiz, C J; Domain, C; Olsson, P; Berthod, E; Becquart, C S
2016-01-01
The damage produced by primary knock-on atoms (PKA) in W has been investigated from the threshold displacement energy (TDE) where it produces one self interstitial atom–vacancy pair to larger energies, up to 100 keV, where a large molten volume is formed. The TDE has been determined in different crystal directions using the Born–Oppenheimer density functional molecular dynamics (DFT-MD). A significant difference has been observed without and with the semi-core electrons. Classical MD has been used with two different empirical potentials characterized as ‘soft’ and ‘hard’ to obtain statistics on TDEs. Cascades of larger energy have been calculated, with these potentials, using a model that accounts for electronic losses (Sand et al 2013 Europhys. Lett. 103 46003). Two other sets of cascades have been produced using the binary collision approximation (BCA): a Monte Carlo BCA using SDTrimSP (Eckstein et al 2011 SDTrimSP: Version 5.00. Report IPP 12/8) (similar to SRIM www.srim.org) and MARLOWE (RSICC Home Page. (https://rsicc.ornl.gov/codes/psr/psr1/psr-137.html) (accessed May, 2014)). The comparison of these sets of cascades gave a recombination distance equal to 12 Å which is significantly larger from the one we reported in Hou et al (2010 J. Nucl. Mater. 403 89) because, here, we used bulk cascades rather than surface cascades which produce more defects (Stoller 2002 J. Nucl. Mater. 307 935, Nordlund et al 1999 Nature 398 49). Investigations on the defect clustering aspect showed that the difference between BCA and MD cascades is considerably reduced after the annealing of the cascade debris at 473 K using our Object Kinetic Monte Carlo model, LAKIMOCA (Domain et al 2004 J. Nucl. Mater. 335 121). (paper)
Approximating distributions from moments
Pawula, R. F.
1987-11-01
A method based upon Pearson-type approximations from statistics is developed for approximating a symmetric probability density function from its moments. The extended Fokker-Planck equation for non-Markov processes is shown to be the underlying foundation for the approximations. The approximation is shown to be exact for the beta probability density function. The applicability of the general method is illustrated by numerous pithy examples from linear and nonlinear filtering of both Markov and non-Markov dichotomous noise. New approximations are given for the probability density function in two cases in which exact solutions are unavailable, those of (i) the filter-limiter-filter problem and (ii) second-order Butterworth filtering of the random telegraph signal. The approximate results are compared with previously published Monte Carlo simulations in these two cases.
Directory of Open Access Journals (Sweden)
V. F. Chekhun
2013-09-01
Full Text Available New data on cytogenetic approximation of the experimental cytogenetic dependence "dose - effect" based on the spline regression model that improves biological dosimetry of human radiological exposure were received. This is achieved by reducing the error of the determination of absorbed dose as compared to the traditional use of linear and linear-quadratic models and makes it possible to predict the effect of dose curves on plateau.
Directory of Open Access Journals (Sweden)
Xin Chen
2015-01-01
Full Text Available Adaptive Dynamic Programming (ADP with critic-actor architecture is an effective way to perform online learning control. To avoid the subjectivity in the design of a neural network that serves as a critic network, kernel-based adaptive critic design (ACD was developed recently. There are two essential issues for a static kernel-based model: how to determine proper hyperparameters in advance and how to select right samples to describe the value function. They all rely on the assessment of sample values. Based on the theoretical analysis, this paper presents a two-phase simultaneous learning method for a Gaussian-kernel-based critic network. It is able to estimate the values of samples without infinitively revisiting them. And the hyperparameters of the kernel model are optimized simultaneously. Based on the estimated sample values, the sample set can be refined by adding alternatives or deleting redundances. Combining this critic design with actor network, we present a Gaussian-kernel-based Adaptive Dynamic Programming (GK-ADP approach. Simulations are used to verify its feasibility, particularly the necessity of two-phase learning, the convergence characteristics, and the improvement of the system performance by using a varying sample set.
A statistical mechanical approach to restricted integer partition functions
Zhou, Chi-Chun; Dai, Wu-Sheng
2018-05-01
The main aim of this paper is twofold: (1) suggesting a statistical mechanical approach to the calculation of the generating function of restricted integer partition functions which count the number of partitions—a way of writing an integer as a sum of other integers under certain restrictions. In this approach, the generating function of restricted integer partition functions is constructed from the canonical partition functions of various quantum gases. (2) Introducing a new type of restricted integer partition functions corresponding to general statistics which is a generalization of Gentile statistics in statistical mechanics; many kinds of restricted integer partition functions are special cases of this restricted integer partition function. Moreover, with statistical mechanics as a bridge, we reveal a mathematical fact: the generating function of restricted integer partition function is just the symmetric function which is a class of functions being invariant under the action of permutation groups. Using this approach, we provide some expressions of restricted integer partition functions as examples.
Directory of Open Access Journals (Sweden)
Xhevat Z. Krasniqi
2015-11-01
Full Text Available In this paper, using rest bounded variation sequences and head bounded variation sequences, some new results on approximation of functions (signals by almost generalized Nörlund means of their Fourier series are obtained. To our best knowledge this the first time to use such classes of sequences on approximations of the type treated in this paper. In addition, several corollaries are derived from our results as well as those obtained previously by others.
Introducing Linear Functions: An Alternative Statistical Approach
Nolan, Caroline; Herbert, Sandra
2015-01-01
The introduction of linear functions is the turning point where many students decide if mathematics is useful or not. This means the role of parameters and variables in linear functions could be considered to be "threshold concepts". There is recognition that linear functions can be taught in context through the exploration of linear…
Green's function approach to the anisotropic Kondo-necklace lattice
International Nuclear Information System (INIS)
Rezania, H.; Langari, A.; Thalmeier, P.
2007-01-01
Full text: We have studied the effect of anisotropy on the quantum phase transition of the 2D anisotropic Kondo necklace lattice [1] within a Green's function approach [2]. In the disordered phase the ground state is the product of all singlet bonds between itinerant and localized spins. It is separated by a finite energy gap from the triplet excited states. The quantum phase transition to the antiferromagnetically ordered phase takes place where the gap vanishes. In this approach we use the bond operator formalism introduced in Ref.[3] where each bond is represented by the singlet and triplet operators. The Kondo necklace Hamiltonian in the bond operator representation is composed of the kinetic energy and pairing part (H2), the two particle interaction (H4) of the boson gas and a term which includes three boson operators (H3). In order to ensure that the physical states are either singlets or triplets we impose the hard-core condition by introducing an infinite on-site repulsion between triplet bosons (H U ). The scattering vertex in the ladder approximation satisfies the Bethe-Salpeter equation [4]. By calculating the scattering vertex function we obtain the self energy contribution of the Hamiltonian H U . We have added the second order contribution of the self energy of H3 to the self energy of H U . It should be noted that the non conservation of triplet boson numbers requires the inclusion of the anomalous Green's functions. We treat H 4 in mean-field theory, by splitting the quartic operator into all possible pairs. Finally we obtain the renormalization of coefficients in the H 2 Hamiltonian and calculate the energy gap. Indeed at the critical point a condensation of triplet bosons occurs. We have numerically found the critical point of this model and compared our results with the corresponding mean field values [5]. Moreover, the critical exponent of the energy gap can be obtained more accurately than the mean field results. (authors)
Sparse approximation with bases
2015-01-01
This book systematically presents recent fundamental results on greedy approximation with respect to bases. Motivated by numerous applications, the last decade has seen great successes in studying nonlinear sparse approximation. Recent findings have established that greedy-type algorithms are suitable methods of nonlinear approximation in both sparse approximation with respect to bases and sparse approximation with respect to redundant systems. These insights, combined with some previous fundamental results, form the basis for constructing the theory of greedy approximation. Taking into account the theoretical and practical demand for this kind of theory, the book systematically elaborates a theoretical framework for greedy approximation and its applications. The book addresses the needs of researchers working in numerical mathematics, harmonic analysis, and functional analysis. It quickly takes the reader from classical results to the latest frontier, but is written at the level of a graduate course and do...
International Nuclear Information System (INIS)
Gawand, Hemangi Laxman; Bhattacharjee, A. K.; Roy, Kallol
2017-01-01
In industrial plants such as nuclear power plants, system operations are performed by embedded controllers orchestrated by Supervisory Control and Data Acquisition (SCADA) software. A targeted attack (also termed a control aware attack) on the controller/SCADA software can lead a control system to operate in an unsafe mode or sometimes to complete shutdown of the plant. Such malware attacks can result in tremendous cost to the organization for recovery, cleanup, and maintenance activity. SCADA systems in operational mode generate huge log files. These files are useful in analysis of the plant behavior and diagnostics during an ongoing attack. However, they are bulky and difficult for manual inspection. Data mining techniques such as least squares approximation and computational methods can be used in the analysis of logs and to take proactive actions when required. This paper explores methodologies and algorithms so as to develop an effective monitoring scheme against control aware cyber attacks. It also explains soft computation techniques such as the computational geometric method and least squares approximation that can be effective in monitor design. This paper provides insights into diagnostic monitoring of its effectiveness by attack simulations on a four-tank model and using computation techniques to diagnose it. Cyber security of instrumentation and control systems used in nuclear power plants is of paramount importance and hence could be a possible target of such applications
Energy Technology Data Exchange (ETDEWEB)
Gawand, Hemangi Laxman [Homi Bhabha National Institute, Computer Section, BARC, Mumbai (India); Bhattacharjee, A. K. [Reactor Control Division, BARC, Mumbai (India); Roy, Kallol [BHAVINI, Kalpakkam (India)
2017-04-15
In industrial plants such as nuclear power plants, system operations are performed by embedded controllers orchestrated by Supervisory Control and Data Acquisition (SCADA) software. A targeted attack (also termed a control aware attack) on the controller/SCADA software can lead a control system to operate in an unsafe mode or sometimes to complete shutdown of the plant. Such malware attacks can result in tremendous cost to the organization for recovery, cleanup, and maintenance activity. SCADA systems in operational mode generate huge log files. These files are useful in analysis of the plant behavior and diagnostics during an ongoing attack. However, they are bulky and difficult for manual inspection. Data mining techniques such as least squares approximation and computational methods can be used in the analysis of logs and to take proactive actions when required. This paper explores methodologies and algorithms so as to develop an effective monitoring scheme against control aware cyber attacks. It also explains soft computation techniques such as the computational geometric method and least squares approximation that can be effective in monitor design. This paper provides insights into diagnostic monitoring of its effectiveness by attack simulations on a four-tank model and using computation techniques to diagnose it. Cyber security of instrumentation and control systems used in nuclear power plants is of paramount importance and hence could be a possible target of such applications.
Directory of Open Access Journals (Sweden)
Hemangi Laxman Gawand
2017-04-01
Full Text Available In industrial plants such as nuclear power plants, system operations are performed by embedded controllers orchestrated by Supervisory Control and Data Acquisition (SCADA software. A targeted attack (also termed a control aware attack on the controller/SCADA software can lead a control system to operate in an unsafe mode or sometimes to complete shutdown of the plant. Such malware attacks can result in tremendous cost to the organization for recovery, cleanup, and maintenance activity. SCADA systems in operational mode generate huge log files. These files are useful in analysis of the plant behavior and diagnostics during an ongoing attack. However, they are bulky and difficult for manual inspection. Data mining techniques such as least squares approximation and computational methods can be used in the analysis of logs and to take proactive actions when required. This paper explores methodologies and algorithms so as to develop an effective monitoring scheme against control aware cyber attacks. It also explains soft computation techniques such as the computational geometric method and least squares approximation that can be effective in monitor design. This paper provides insights into diagnostic monitoring of its effectiveness by attack simulations on a four-tank model and using computation techniques to diagnose it. Cyber security of instrumentation and control systems used in nuclear power plants is of paramount importance and hence could be a possible target of such applications.
Schmidt, Wolfgang M
1980-01-01
"In 1970, at the U. of Colorado, the author delivered a course of lectures on his famous generalization, then just established, relating to Roth's theorem on rational approxi- mations to algebraic numbers. The present volume is an ex- panded and up-dated version of the original mimeographed notes on the course. As an introduction to the author's own remarkable achievements relating to the Thue-Siegel-Roth theory, the text can hardly be bettered and the tract can already be regarded as a classic in its field."(Bull.LMS) "Schmidt's work on approximations by algebraic numbers belongs to the deepest and most satisfactory parts of number theory. These notes give the best accessible way to learn the subject. ... this book is highly recommended." (Mededelingen van het Wiskundig Genootschap)
Functional approach to a time-dependent self-consistent field theory
International Nuclear Information System (INIS)
Reinhardt, H.
1979-01-01
The time-dependent Hartree-Fock approximation is formulated within the path integral approach. It is shown that by a suitable choice of the collective field the classical equation of motion of the collective field coincides with the time-dependent Hartree (TDH) equation. The consideration is restricted to the TDH equation, since the exchange terms do not appear in the functional approach on the same footing as the direct terms
Directory of Open Access Journals (Sweden)
Paul Kussmaul
2008-04-01
Full Text Available In the early phase of translation studies in Germany, contrastive linguistics played a major role. I shall briefly describe this approach so that the functional approach will become clearer by contrast. Influenced by the representatives of stylistique comparée, Vinay/Darbelnet (1968 Wolfram Wilss, for instance, in his early work (1971, 1977 makes frequent use of the notion transposition (German “Ausdrucksverschiebung“, cf. also Catford’s (1965 term shift. As a whole, of course, Wilss’ work has a much broader scope. More recently, he has investigated the role of cognition (1988 and the various factors in translator behaviour (1996. Nevertheless, transposition is still a very important and useful notion in describing the translation process. The need for transpositions arises when there is no possibility of formal one-to-one correspondence between source and target-language structures. The basic idea is that whenever there is a need for transposition, we are faced with a translation problem. In the early phase of translation studies in Germany, contrastive linguistics played a major role. I shall briefly describe this approach so that the functional approach will become clearer by contrast. Influenced by the representatives of stylistique comparée, Vinay/Darbelnet (1968 Wolfram Wilss, for instance, in his early work (1971, 1977 makes frequent use of the notion transposition (German “Ausdrucksverschiebung“, cf. also Catford’s (1965 term shift. As a whole, of course, Wilss’ work has a much broader scope. More recently, he has investigated the role of cognition (1988 and the various factors in translator behaviour (1996. Nevertheless, transposition is still a very important and useful notion in describing the translation process. The need for transpositions arises when there is no possibility of formal one-to-one correspondence between source and target-language structures. The basic idea is that whenever there is a need for
A systemic approach for modeling soil functions
Vogel, Hans-Jörg; Bartke, Stephan; Daedlow, Katrin; Helming, Katharina; Kögel-Knabner, Ingrid; Lang, Birgit; Rabot, Eva; Russell, David; Stößel, Bastian; Weller, Ulrich; Wiesmeier, Martin; Wollschläger, Ute
2018-03-01
The central importance of soil for the functioning of terrestrial systems is increasingly recognized. Critically relevant for water quality, climate control, nutrient cycling and biodiversity, soil provides more functions than just the basis for agricultural production. Nowadays, soil is increasingly under pressure as a limited resource for the production of food, energy and raw materials. This has led to an increasing demand for concepts assessing soil functions so that they can be adequately considered in decision-making aimed at sustainable soil management. The various soil science disciplines have progressively developed highly sophisticated methods to explore the multitude of physical, chemical and biological processes in soil. It is not obvious, however, how the steadily improving insight into soil processes may contribute to the evaluation of soil functions. Here, we present to a new systemic modeling framework that allows for a consistent coupling between reductionist yet observable indicators for soil functions with detailed process understanding. It is based on the mechanistic relationships between soil functional attributes, each explained by a network of interacting processes as derived from scientific evidence. The non-linear character of these interactions produces stability and resilience of soil with respect to functional characteristics. We anticipate that this new conceptional framework will integrate the various soil science disciplines and help identify important future research questions at the interface between disciplines. It allows the overwhelming complexity of soil systems to be adequately coped with and paves the way for steadily improving our capability to assess soil functions based on scientific understanding.
Reduced density matrix functional theory via a wave function based approach
Energy Technology Data Exchange (ETDEWEB)
Schade, Robert; Bloechl, Peter [Institute for Theoretical Physics, Clausthal University of Technology, Clausthal (Germany); Pruschke, Thomas [Institute for Theoretical Physics, University of Goettingen, Goettingen (Germany)
2016-07-01
We propose a new method for the calculation of the electronic and atomic structure of correlated electron systems based on reduced density matrix functional theory (rDMFT). The density-matrix functional is evaluated on the fly using Levy's constrained search formalism. The present implementation rests on a local approximation of the interaction reminiscent to that of dynamical mean field theory (DMFT). We focus here on additional approximations to the exact density-matrix functional in the local approximation and evaluate their performance.
Messica, A.
2016-10-01
The probability distribution function of a weighted sum of non-identical lognormal random variables is required in various fields of science and engineering and specifically in finance for portfolio management as well as exotic options valuation. Unfortunately, it has no known closed form and therefore has to be approximated. Most of the approximations presented to date are complex as well as complicated for implementation. This paper presents a simple, and easy to implement, approximation method via modified moments matching and a polynomial asymptotic series expansion correction for a central limit theorem of a finite sum. The method results in an intuitively-appealing and computation-efficient approximation for a finite sum of lognormals of at least ten summands and naturally improves as the number of summands increases. The accuracy of the method is tested against the results of Monte Carlo simulationsand also compared against the standard central limit theorem andthe commonly practiced Markowitz' portfolio equations.
Approximation techniques for engineers
Komzsik, Louis
2006-01-01
Presenting numerous examples, algorithms, and industrial applications, Approximation Techniques for Engineers is your complete guide to the major techniques used in modern engineering practice. Whether you need approximations for discrete data of continuous functions, or you''re looking for approximate solutions to engineering problems, everything you need is nestled between the covers of this book. Now you can benefit from Louis Komzsik''s years of industrial experience to gain a working knowledge of a vast array of approximation techniques through this complete and self-contained resource.
Form Follows Function. A new approach to determining vessel function
Directory of Open Access Journals (Sweden)
Vincent van der Veen
2018-05-01
Full Text Available In this article I present a theoretical model for assigning functions to categories of Roman ceramics. This model was designed to make broad statements about assemblages that are too large to analyse in detail. It is therefore based on the 'ideal use' of a vessel - i.e. the function the potter had in mind when he chose the clay, temper, forming techniques and so on - rather than 'non-ideal' or actual use. Characteristics considered are, among others, shape, size, weight, surface treatment and wall thickness. Seven distinct functions have been identified, taking the inherent multi-functionality of certain vessels into account. In many cases an individual vessel type will be suitable for more than one function. In a case study the commonly made functional distinction between smooth-tempered one-handled flagons (kruiken as tableware and two-handled flagons (kruikamforen as storage vessels is challenged. Furthermore, differences in their deposition within both grave and settlement assemblages are explored.
Traa, M.R.M.J.; Traa, M.R.M.J.; Caspers, W.J.; Caspers, W.J.; Banning, E.J.; Banning, E.J.
1994-01-01
In this paper the Hubbard-Anderson model on a square lattice with two holes is studied. The ground state (GS) is approximated by a variational RVB-type wave function. The holes interact by exchange of a localized spin excitation (SE), which is created or absorbed if a hole moves to a
Integral equations of hadronic correlation functions a functional- bootstrap approach
Manesis, E K
1974-01-01
A reasonable 'microscopic' foundation of the Feynman hadron-liquid analogy is offered, based on a class of models for hadron production. In an external field formalism, the equivalence (complementarity) of the exclusive and inclusive descriptions of hadronic reactions is specifically expressed in a functional-bootstrap form, and integral equations between inclusive and exclusive correlation functions are derived. Using the latest CERN-ISR data on the two-pion inclusive correlation function, and assuming rapidity translational invariance for the exclusive one, the simplest integral equation is solved in the 'central region' and an exclusive correlation length in rapidity predicted. An explanation is also offered for the unexpected similarity observed between pi /sup +/ pi /sup -/ and pi /sup -/ pi /sup -/ inclusive correlations. (31 refs).
Nobile, F.
2015-10-30
In this work we provide a convergence analysis for the quasi-optimal version of the sparse-grids stochastic collocation method we presented in a previous work: “On the optimal polynomial approximation of stochastic PDEs by Galerkin and collocation methods” (Beck et al., Math Models Methods Appl Sci 22(09), 2012). The construction of a sparse grid is recast into a knapsack problem: a profit is assigned to each hierarchical surplus and only the most profitable ones are added to the sparse grid. The convergence rate of the sparse grid approximation error with respect to the number of points in the grid is then shown to depend on weighted summability properties of the sequence of profits. This is a very general argument that can be applied to sparse grids built with any uni-variate family of points, both nested and non-nested. As an example, we apply such quasi-optimal sparse grids to the solution of a particular elliptic PDE with stochastic diffusion coefficients, namely the “inclusions problem”: we detail the convergence estimates obtained in this case using polynomial interpolation on either nested (Clenshaw–Curtis) or non-nested (Gauss–Legendre) abscissas, verify their sharpness numerically, and compare the performance of the resulting quasi-optimal grids with a few alternative sparse-grid construction schemes recently proposed in the literature.
Nobile, F.; Tamellini, L.; Tempone, Raul
2015-01-01
In this work we provide a convergence analysis for the quasi-optimal version of the sparse-grids stochastic collocation method we presented in a previous work: “On the optimal polynomial approximation of stochastic PDEs by Galerkin and collocation methods” (Beck et al., Math Models Methods Appl Sci 22(09), 2012). The construction of a sparse grid is recast into a knapsack problem: a profit is assigned to each hierarchical surplus and only the most profitable ones are added to the sparse grid. The convergence rate of the sparse grid approximation error with respect to the number of points in the grid is then shown to depend on weighted summability properties of the sequence of profits. This is a very general argument that can be applied to sparse grids built with any uni-variate family of points, both nested and non-nested. As an example, we apply such quasi-optimal sparse grids to the solution of a particular elliptic PDE with stochastic diffusion coefficients, namely the “inclusions problem”: we detail the convergence estimates obtained in this case using polynomial interpolation on either nested (Clenshaw–Curtis) or non-nested (Gauss–Legendre) abscissas, verify their sharpness numerically, and compare the performance of the resulting quasi-optimal grids with a few alternative sparse-grid construction schemes recently proposed in the literature.
Li, Shaohong L; Truhlar, Donald G
2015-07-14
Time-dependent density functional theory (TDDFT) with conventional local and hybrid functionals such as the local and hybrid generalized gradient approximations (GGA) seriously underestimates the excitation energies of Rydberg states, which limits its usefulness for applications such as spectroscopy and photochemistry. We present here a scheme that modifies the exchange-enhancement factor to improve GGA functionals for Rydberg excitations within the TDDFT framework while retaining their accuracy for valence excitations and for the thermochemical energetics calculated by ground-state density functional theory. The scheme is applied to a popular hybrid GGA functional and tested on data sets of valence and Rydberg excitations and atomization energies, and the results are encouraging. The scheme is simple and flexible. It can be used to correct existing functionals, and it can also be used as a strategy for the development of new functionals.
Exponentiation for products of Wilson lines within the generating function approach
International Nuclear Information System (INIS)
Vladimirov, A.A.
2015-01-01
We present the generating function approach to the perturbative exponentiation of correlators of a product of Wilson lines and loops. The exponentiated expression is presented in closed form as an algebraic function of correlators of known operators, which can be seen as a generating function for web diagrams. The expression is naturally split onto two parts: the exponentiation kernel, which accumulates all non-trivial information about web diagrams, and the defect of exponentiation, which reconstructs the matrix exponent and is a function of the exponentiation kernel. The detailed comparison of the presented approach with existing approaches to exponentiation is presented as well. We also give examples of calculations within the generating function exponentiation, namely, we consider different configurations of light-like Wilson lines in the multi-gluon-exchange-webs (MGEW) approximation. Within this approximation the corresponding correlators can be calculated exactly at any order of perturbative expansion by only algebraic manipulations. The MGEW approximation shows violation of the dipole formula for infrared singularities at three-loop order.
Identifying Similarities in Cognitive Subtest Functional Requirements: An Empirical Approach
Frisby, Craig L.; Parkin, Jason R.
2007-01-01
In the cognitive test interpretation literature, a Rational/Intuitive, Indirect Empirical, or Combined approach is typically used to construct conceptual taxonomies of the functional (behavioral) similarities between subtests. To address shortcomings of these approaches, the functional requirements for 49 subtests from six individually…
A new approach to the logistic function with some applications
Rzadkowski, Grzegorz; Głażewska, Iwona; Sawińska, Katarzyna
2014-01-01
In the present paper we propose a new approach to investigate the logistic function, commonly used in mathematical models in economics and management. The approach is based on indicating in a given time series, having a logistic trend, some characteristic points corresponding to zeroes of successive derivatives of the logistic function. We give also examples of application of this method.
Green's function approach to neutron flux discontinuities
International Nuclear Information System (INIS)
Saad, E.A.; El-Wakil, S.A.
1980-01-01
The present work is devoted to the presentation of analytical method for the calculation of elastically and inelastically slowed down neutrons in an infinite non-absorbing medium. On the basis of the central limit theory (CLT) and the integral transform technique the slowing down equation including inelastic scattering, in terms of the Green function of elastic scattering, is solved. The Green function is decomposed according to the number of collisions. Placzec discontinuity associated with elastic scattering in addition to two discontinuities due to inelastic scattering are investigated. Numerical calculations for Fe 56 show that the elastic discontinuity produces about 41.8% change in the collision density whilst the ratio of the inelastic collision density discontinuity at qsub(o)sup(+) to the Placzec discontinuity at usub(o) + 1n 1/oc gives 55.7 percent change. (author)
Functional coatings: the sol-gel approach
International Nuclear Information System (INIS)
Belleville, Ph.
2010-01-01
CEA's sol-gel laboratory is specialized in the development of innovative sol-gel optical coatings and has extended its application field to membrane materials and coatings for energy conversion, to electric coatings for microelectronics devices and to thin films for gas sensing. This article describes, by way of examples, the laboratory's research on sol-gel functional coatings, including nano-material synthesis, organic-inorganic hybrid-based solution preparation as well as deposition process development and prototyping. (author)
Reduced kinetic equations: An influence functional approach
International Nuclear Information System (INIS)
Wio, H.S.
1985-01-01
The author discusses a scheme for obtaining reduced descriptions of multivariate kinetic equations based on the 'influence functional' method of Feynmann. It is applied to the case of Fokker-Planck equations showing the form that results for the reduced equation. The possibility of Markovian or non-Markovian reduced description is discussed. As a particular example, the reduction of the Kramers equation to the Smoluchwski equation in the limit of high friction is also discussed
Quantum thermodynamics: a nonequilibrium Green's function approach.
Esposito, Massimiliano; Ochoa, Maicol A; Galperin, Michael
2015-02-27
We establish the foundations of a nonequilibrium theory of quantum thermodynamics for noninteracting open quantum systems strongly coupled to their reservoirs within the framework of the nonequilibrium Green's functions. The energy of the system and its coupling to the reservoirs are controlled by a slow external time-dependent force treated to first order beyond the quasistatic limit. We derive the four basic laws of thermodynamics and characterize reversible transformations. Stochastic thermodynamics is recovered in the weak coupling limit.
Cheng, Long; Hou, Zeng-Guang; Tan, Min; Zhang, W J
2012-10-01
The trajectory tracking problem of a closed-chain five-bar robot is studied in this paper. Based on an error transformation function and the backstepping technique, an approximation-based tracking algorithm is proposed, which can guarantee the control performance of the robotic system in both the stable and transient phases. In particular, the overshoot, settling time, and final tracking error of the robotic system can be all adjusted by properly setting the parameters in the error transformation function. The radial basis function neural network (RBFNN) is used to compensate the complicated nonlinear terms in the closed-loop dynamics of the robotic system. The approximation error of the RBFNN is only required to be bounded, which simplifies the initial "trail-and-error" configuration of the neural network. Illustrative examples are given to verify the theoretical analysis and illustrate the effectiveness of the proposed algorithm. Finally, it is also shown that the proposed approximation-based controller can be simplified by a smart mechanical design of the closed-chain robot, which demonstrates the promise of the integrated design and control philosophy.
Self-similar factor approximants
International Nuclear Information System (INIS)
Gluzman, S.; Yukalov, V.I.; Sornette, D.
2003-01-01
The problem of reconstructing functions from their asymptotic expansions in powers of a small variable is addressed by deriving an improved type of approximants. The derivation is based on the self-similar approximation theory, which presents the passage from one approximant to another as the motion realized by a dynamical system with the property of group self-similarity. The derived approximants, because of their form, are called self-similar factor approximants. These complement the obtained earlier self-similar exponential approximants and self-similar root approximants. The specific feature of self-similar factor approximants is that their control functions, providing convergence of the computational algorithm, are completely defined from the accuracy-through-order conditions. These approximants contain the Pade approximants as a particular case, and in some limit they can be reduced to the self-similar exponential approximants previously introduced by two of us. It is proved that the self-similar factor approximants are able to reproduce exactly a wide class of functions, which include a variety of nonalgebraic functions. For other functions, not pertaining to this exactly reproducible class, the factor approximants provide very accurate approximations, whose accuracy surpasses significantly that of the most accurate Pade approximants. This is illustrated by a number of examples showing the generality and accuracy of the factor approximants even when conventional techniques meet serious difficulties
DEFF Research Database (Denmark)
Senjean, Bruno; Knecht, Stefan; Jensen, Hans Jørgen Aa
2015-01-01
Gross-Oliveira-Kohn density-functional theory (GOK-DFT) for ensembles is, in principle, very attractive but has been hard to use in practice. A practical model based on GOK-DFT for the calculation of electronic excitation energies is discussed. The model relies on two modifications of GOK-DFT: use...... promising results have been obtained for both single (including charge transfer) and double excitations with spin-independent short-range local and semilocal functionals. Even at the Kohn-Sham ensemble DFT level, which is recovered when the range-separation parameter is set to 0, LIM performs better than...
International Nuclear Information System (INIS)
Giricheva, N.I.; Girichev, G.V.; Smorodin, S.V.
2007-01-01
Scanning of potential energy surface in the LaI 3 molecule along normal coordinates are realized using the B3LYP/SDD,SDD method. The most anharmonicity is shown to have a potential function of non-planar oscillation ν 2 (A 2 ''). Effect of anharmonicity on the value of mean-square oscillation amplitudes and oscillation spectrum of the molecule is established. It is noted that the account of anharmonicity of potential functions leads to decreasing mean-square oscillation amplitudes [ru
A Constructive Sharp Approach to Functional Quantization of Stochastic Processes
Junglen, Stefan; Luschgy, Harald
2010-01-01
We present a constructive approach to the functional quantization problem of stochastic processes, with an emphasis on Gaussian processes. The approach is constructive, since we reduce the infinite-dimensional functional quantization problem to a finite-dimensional quantization problem that can be solved numerically. Our approach achieves the sharp rate of the minimal quantization error and can be used to quantize the path space for Gaussian processes and also, for example, Lévy processes.
On Convex Quadratic Approximation
den Hertog, D.; de Klerk, E.; Roos, J.
2000-01-01
In this paper we prove the counterintuitive result that the quadratic least squares approximation of a multivariate convex function in a finite set of points is not necessarily convex, even though it is convex for a univariate convex function. This result has many consequences both for the field of
A Multivariate Approach to Functional Neuro Modeling
DEFF Research Database (Denmark)
Mørch, Niels J.S.
1998-01-01
by the application of linear and more flexible, nonlinear microscopic regression models to a real-world dataset. The dependency of model performance, as quantified by generalization error, on model flexibility and training set size is demonstrated, leading to the important realization that no uniformly optimal model......, provides the basis for a generalization theoretical framework relating model performance to model complexity and dataset size. Briefly summarized the major topics discussed in the thesis include: - An introduction of the representation of functional datasets by pairs of neuronal activity patterns...... exists. - Model visualization and interpretation techniques. The simplicity of this task for linear models contrasts the difficulties involved when dealing with nonlinear models. Finally, a visualization technique for nonlinear models is proposed. A single observation emerges from the thesis...
An approach to the structure function for nucleon
International Nuclear Information System (INIS)
Long Ming
1986-01-01
The structure function for nucleon is discussed by using the method given in a previous paper. The formula are compared with the experimental data from low Q 2 to high Q 2 . The results show that the way that the structure function for nucleon can be obtained from the hadronic wavefunction is a possible approach of investigating structure functions for hadron
Chen, Xin; Xie, Penghuan; Xiong, Yonghua; He, Yong; Wu, Min
2015-01-01
Adaptive Dynamic Programming (ADP) with critic-actor architecture is an effective way to perform online learning control. To avoid the subjectivity in the design of a neural network that serves as a critic network, kernel-based adaptive critic design (ACD) was developed recently. There are two essential issues for a static kernel-based model: how to determine proper hyperparameters in advance and how to select right samples to describe the value function. They all rely on the assessment of sa...
Capillary condensation in pores with rough walls: a density functional approach.
Bryk, P; Rzysko, W; Malijevsky, Al; Sokołowski, S
2007-09-01
The effect of surface roughness of slit-like pore walls on the capillary condensation of a spherical particles and short chains is studied. The gas molecules interact with the substrate by a Lennard-Jones (9,3) potential. The rough layer at each pore wall has a variable thickness and density and consists of a disordered quenched matrix of spherical particles. The system is described in the framework of a density functional approach and using computer simulations. The contribution due to attractive van der Waals interactions between adsorbate molecules is described by using first-order mean spherical approximation and mean-field approximation.
Toward Intelligent Hemodynamic Monitoring: A Functional Approach
Directory of Open Access Journals (Sweden)
Pierre Squara
2012-01-01
Full Text Available Technology is now available to allow a complete haemodynamic analysis; however this is only used in a small proportion of patients and seems to occur when the medical staff have the time and inclination. As a result of this, significant delays occur between an event, its diagnosis and therefore, any treatment required. We can speculate that we should be able to collect enough real time information to make a complete, real time, haemodynamic diagnosis in all critically ill patients. This article advocates for “intelligent haemodynamic monitoring”. Following the steps of a functional analysis, we answered six basic questions. (1 What is the actual best theoretical model for describing haemodynamic disorders? (2 What are the needed and necessary input/output data for describing this model? (3 What are the specific quality criteria and tolerances for collecting each input variable? (4 Based on these criteria, what are the validated available technologies for monitoring each input variable, continuously, real time, and if possible non-invasively? (5 How can we integrate all the needed reliably monitored input variables into the same system for continuously describing the global haemodynamic model? (6 Is it possible to implement this global model into intelligent programs that are able to differentiate clinically relevant changes as opposed to artificial changes and to display intelligent messages and/or diagnoses?
A New Approach for Predicting the Variance of Random Decrement Functions
DEFF Research Database (Denmark)
Asmussen, J. C.; Brincker, Rune
mean Gaussian distributed processes the RD functions are proportional to the correlation functions of the processes. If a linear structur is loaded by Gaussian white noise the modal parameters can be extracted from the correlation funtions of the response, only. One of the weaknesses of the RD...... technique is that no consistent approach to estimate the variance of the RD functions is known. Only approximate relations are available, which can only be used under special conditions. The variance of teh RD functions contains valuable information about accuracy of the estimates. Furthermore, the variance...... can be used as basis for a decision about how many time lags from the RD funtions should be used in the modal parameter extraction procedure. This paper suggests a new method for estimating the variance of the RD functions. The method is consistent in the sense that the accuracy of the approach...
A New Approach for Predicting the Variance of Random Decrement Functions
DEFF Research Database (Denmark)
Asmussen, J. C.; Brincker, Rune
1998-01-01
mean Gaussian distributed processes the RD functions are proportional to the correlation functions of the processes. If a linear structur is loaded by Gaussian white noise the modal parameters can be extracted from the correlation funtions of the response, only. One of the weaknesses of the RD...... technique is that no consistent approach to estimate the variance of the RD functions is known. Only approximate relations are available, which can only be used under special conditions. The variance of teh RD functions contains valuable information about accuracy of the estimates. Furthermore, the variance...... can be used as basis for a decision about how many time lags from the RD funtions should be used in the modal parameter extraction procedure. This paper suggests a new method for estimating the variance of the RD functions. The method is consistent in the sense that the accuracy of the approach...
Spline approximation, Part 1: Basic methodology
Ezhov, Nikolaj; Neitzel, Frank; Petrovic, Svetozar
2018-04-01
In engineering geodesy point clouds derived from terrestrial laser scanning or from photogrammetric approaches are almost never used as final results. For further processing and analysis a curve or surface approximation with a continuous mathematical function is required. In this paper the approximation of 2D curves by means of splines is treated. Splines offer quite flexible and elegant solutions for interpolation or approximation of "irregularly" distributed data. Depending on the problem they can be expressed as a function or as a set of equations that depend on some parameter. Many different types of splines can be used for spline approximation and all of them have certain advantages and disadvantages depending on the approximation problem. In a series of three articles spline approximation is presented from a geodetic point of view. In this paper (Part 1) the basic methodology of spline approximation is demonstrated using splines constructed from ordinary polynomials and splines constructed from truncated polynomials. In the forthcoming Part 2 the notion of B-spline will be explained in a unique way, namely by using the concept of convex combinations. The numerical stability of all spline approximation approaches as well as the utilization of splines for deformation detection will be investigated on numerical examples in Part 3.
Continuation of probability density functions using a generalized Lyapunov approach
Energy Technology Data Exchange (ETDEWEB)
Baars, S., E-mail: s.baars@rug.nl [Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, P.O. Box 407, 9700 AK Groningen (Netherlands); Viebahn, J.P., E-mail: viebahn@cwi.nl [Centrum Wiskunde & Informatica (CWI), P.O. Box 94079, 1090 GB, Amsterdam (Netherlands); Mulder, T.E., E-mail: t.e.mulder@uu.nl [Institute for Marine and Atmospheric research Utrecht, Department of Physics and Astronomy, Utrecht University, Princetonplein 5, 3584 CC Utrecht (Netherlands); Kuehn, C., E-mail: ckuehn@ma.tum.de [Technical University of Munich, Faculty of Mathematics, Boltzmannstr. 3, 85748 Garching bei München (Germany); Wubs, F.W., E-mail: f.w.wubs@rug.nl [Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, P.O. Box 407, 9700 AK Groningen (Netherlands); Dijkstra, H.A., E-mail: h.a.dijkstra@uu.nl [Institute for Marine and Atmospheric research Utrecht, Department of Physics and Astronomy, Utrecht University, Princetonplein 5, 3584 CC Utrecht (Netherlands); School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY (United States)
2017-05-01
Techniques from numerical bifurcation theory are very useful to study transitions between steady fluid flow patterns and the instabilities involved. Here, we provide computational methodology to use parameter continuation in determining probability density functions of systems of stochastic partial differential equations near fixed points, under a small noise approximation. Key innovation is the efficient solution of a generalized Lyapunov equation using an iterative method involving low-rank approximations. We apply and illustrate the capabilities of the method using a problem in physical oceanography, i.e. the occurrence of multiple steady states of the Atlantic Ocean circulation.
Rao, D V; Brunetti, A; Gigante, G E; Takeda, T; Itai, Y; Akatsuka, T
2002-01-01
A new approach is developed to estimate the geometrical factors, solid angle approximation and geometrical efficiency for a system with experimental arrangements using X-ray tube and secondary target as an excitation source in order to produce the nearly monoenergetic K alpha radiation to excite the sample. The variation of the solid angle is studied by changing the radius and length of the collimators towards and away from the source and sample. From these values the variation of the total solid angle and geometrical efficiency is deduced and the optimum value is used for the experimental work. (authors)
Energy Technology Data Exchange (ETDEWEB)
Rao, D.V.; Cesareo, R.; Brunetti, A. [Sassari University, Istituto di Matematica e Fisica (Italy); Gigante, G.E. [Roma Universita, Dipt. di Fisica (Italy); Takeda, T.; Itai, Y. [Tsukuba Univ., Ibaraki (Japan). Inst. of Clinical Medicine; Akatsuka, T. [Yamagata Univ., Yonezawa (Japan). Faculty of Engineering
2002-10-01
A new approach is developed to estimate the geometrical factors, solid angle approximation and geometrical efficiency for a system with experimental arrangements using X-ray tube and secondary target as an excitation source in order to produce the nearly monoenergetic K{alpha} radiation to excite the sample. The variation of the solid angle is studied by changing the radius and length of the collimators towards and away from the source and sample. From these values the variation of the total solid angle and geometrical efficiency is deduced and the optimum value is used for the experimental work. (authors)
Rao, D. V.; Cesareo, R.; Brunetti, A.; Gigante, G. E.; Takeda, T.; Itai, Y.; Akatsuka, T.
2002-10-01
A new approach is developed to estimate the geometrical factors, solid angle approximation and geometrical efficiency for a system with experimental arrangements using X-ray tube and secondary target as an excitation source in order to produce the nearly monoenergetic Kα radiation to excite the sample. The variation of the solid angle is studied by changing the radius and length of the collimators towards and away from the source and sample. From these values the variation of the total solid angle and geometrical efficiency is deduced and the optimum value is used for the experimental work.
Spherical Approximation on Unit Sphere
Directory of Open Access Journals (Sweden)
Eman Samir Bhaya
2018-01-01
Full Text Available In this paper we introduce a Jackson type theorem for functions in LP spaces on sphere And study on best approximation of functions in spaces defined on unit sphere. our central problem is to describe the approximation behavior of functions in spaces for by modulus of smoothness of functions.
Unambiguous results from variational matrix Pade approximants
International Nuclear Information System (INIS)
Pindor, Maciej.
1979-10-01
Variational Matrix Pade Approximants are studied as a nonlinear variational problem. It is shown that although a stationary value of the Schwinger functional is a stationary value of VMPA, the latter has also another stationary value. It is therefore proposed that instead of looking for a stationary point of VMPA, one minimizes some non-negative functional and then one calculates VMPA at the point where the former has the absolute minimum. This approach, which we call the Method of the Variational Gradient (MVG) gives unambiguous results and is also shown to minimize a distance between the approximate and the exact stationary values of the Schwinger functional
Sergeev, A.; Alharbi, F. H.; Jovanovic, R.; Kais, S.
2016-04-01
The gradient expansion of the kinetic energy density functional, when applied to atoms or finite systems, usually grossly overestimates the energy in the fourth order and generally diverges in the sixth order. We avoid the divergence of the integral by replacing the asymptotic series including the sixth order term in the integrand by a rational function. Padé approximants show moderate improvements in accuracy in comparison with partial sums of the series. The results are discussed for atoms and Hooke’s law model for two-electron atoms.
Defining mental disorder. Exploring the 'natural function' approach
Directory of Open Access Journals (Sweden)
Varga Somogy
2011-01-01
Full Text Available Abstract Due to several socio-political factors, to many psychiatrists only a strictly objective definition of mental disorder, free of value components, seems really acceptable. In this paper, I will explore a variant of such an objectivist approach to defining metal disorder, natural function objectivism. Proponents of this approach make recourse to the notion of natural function in order to reach a value-free definition of mental disorder. The exploration of Christopher Boorse's 'biostatistical' account of natural function (1 will be followed an investigation of the 'hybrid naturalism' approach to natural functions by Jerome Wakefield (2. In the third part, I will explore two proposals that call into question the whole attempt to define mental disorder (3. I will conclude that while 'natural function objectivism' accounts fail to provide the backdrop for a reliable definition of mental disorder, there is no compelling reason to conclude that a definition cannot be achieved.
Defining mental disorder. Exploring the 'natural function' approach.
Varga, Somogy
2011-01-21
Due to several socio-political factors, to many psychiatrists only a strictly objective definition of mental disorder, free of value components, seems really acceptable. In this paper, I will explore a variant of such an objectivist approach to defining metal disorder, natural function objectivism. Proponents of this approach make recourse to the notion of natural function in order to reach a value-free definition of mental disorder. The exploration of Christopher Boorse's 'biostatistical' account of natural function (1) will be followed an investigation of the 'hybrid naturalism' approach to natural functions by Jerome Wakefield (2). In the third part, I will explore two proposals that call into question the whole attempt to define mental disorder (3). I will conclude that while 'natural function objectivism' accounts fail to provide the backdrop for a reliable definition of mental disorder, there is no compelling reason to conclude that a definition cannot be achieved.
AN ENERGY FUNCTION APPROACH FOR FINDING ROOTS OF CHARACTERISTIC EQUATION
Deepak Mishra; Prem K. Kalra
2011-01-01
In this paper, an energy function approach for finding roots of a characteristic equation has been proposed. Finding the roots of a characteristics equation is considered as an optimization problem. We demonstrated that this problem can be solved with the application of feedback type neural network. The proposed approach is fast and robust against variation of parameter.
Combining formal and functional approaches to topic structure
Zellers, M.; Post, B.
2012-01-01
Fragmentation between formal and functional approaches to prosodic variation is an ongoing problem in linguistic research. In particular, the frameworks of the Phonetics of Talk-in-Interaction (PTI) and Empirical Phonology (EP) take very different theoretical and methodological approaches to this
Combining Formal and Functional Approaches to Topic Structure
Zellers, Margaret; Post, Brechtje
2012-01-01
Fragmentation between formal and functional approaches to prosodic variation is an ongoing problem in linguistic research. In particular, the frameworks of the Phonetics of Talk-in-Interaction (PTI) and Empirical Phonology (EP) take very different theoretical and methodological approaches to this kind of variation. We argue that it is fruitful to…
A Comprehensive Approach for Pectin Chemical and Functional Characterization
DEFF Research Database (Denmark)
de Sousa, António Felipe Gomes Teixeira
In this work, a comprehensive approach for the chemical and functional analysis of pectin was used in order to relate the different extraction conditions used to the polymer structure and the final functional (mainly gelling) properties. A wide range of methods were utilized including chemical an...
Approximate kernel competitive learning.
Wu, Jian-Sheng; Zheng, Wei-Shi; Lai, Jian-Huang
2015-03-01
Kernel competitive learning has been successfully used to achieve robust clustering. However, kernel competitive learning (KCL) is not scalable for large scale data processing, because (1) it has to calculate and store the full kernel matrix that is too large to be calculated and kept in the memory and (2) it cannot be computed in parallel. In this paper we develop a framework of approximate kernel competitive learning for processing large scale dataset. The proposed framework consists of two parts. First, it derives an approximate kernel competitive learning (AKCL), which learns kernel competitive learning in a subspace via sampling. We provide solid theoretical analysis on why the proposed approximation modelling would work for kernel competitive learning, and furthermore, we show that the computational complexity of AKCL is largely reduced. Second, we propose a pseudo-parallelled approximate kernel competitive learning (PAKCL) based on a set-based kernel competitive learning strategy, which overcomes the obstacle of using parallel programming in kernel competitive learning and significantly accelerates the approximate kernel competitive learning for large scale clustering. The empirical evaluation on publicly available datasets shows that the proposed AKCL and PAKCL can perform comparably as KCL, with a large reduction on computational cost. Also, the proposed methods achieve more effective clustering performance in terms of clustering precision against related approximate clustering approaches. Copyright © 2014 Elsevier Ltd. All rights reserved.
International Conference Approximation Theory XV
Schumaker, Larry
2017-01-01
These proceedings are based on papers presented at the international conference Approximation Theory XV, which was held May 22–25, 2016 in San Antonio, Texas. The conference was the fifteenth in a series of meetings in Approximation Theory held at various locations in the United States, and was attended by 146 participants. The book contains longer survey papers by some of the invited speakers covering topics such as compressive sensing, isogeometric analysis, and scaling limits of polynomials and entire functions of exponential type. The book also includes papers on a variety of current topics in Approximation Theory drawn from areas such as advances in kernel approximation with applications, approximation theory and algebraic geometry, multivariate splines for applications, practical function approximation, approximation of PDEs, wavelets and framelets with applications, approximation theory in signal processing, compressive sensing, rational interpolation, spline approximation in isogeometric analysis, a...
Rasero Causil, Diego; Ortega López, César; Espitia Rico, Miguel
2018-04-01
Computational calculations of total energy based on density functional theory were used to investigate the structural, electronic, and magnetic properties of the DyB2 compounds in the hexagonal structure. The calculations were carried out by means of the full-potential linearized augmented plane wave (FP-LAPW) method, employing the computational Wien2k package. The local density approximation (LDA) and the generalized gradient approximation (GGA) were used for the electron-electron interactions. Additionally, we used the functional hybrid PBE0 for a better description the electronic and magnetic properties, because the DyB2 compound is a strongly-correlated system. We found that the calculated lattice constant agrees well with the values reported theoretically and experimentally. The density of states (DOS) calculation shows that the compound exhibits a metallic behavior and has magnetic properties, with a total magnetic moment of 5.47 μ0/cell determined mainly by the 4f states of the rare earth elements. The functional PBE0 shows a strong localization of the Dy-4f orbitals.
Cioslowski, Jerzy; Strasburger, Krzysztof
2018-04-01
Electronic properties of several states of the five- and six-electron harmonium atoms are obtained from large-scale calculations employing explicitly correlated basis functions. The high accuracy of the computed energies (including their components), natural spinorbitals, and their occupation numbers makes them suitable for testing, calibration, and benchmarking of approximate formalisms of quantum chemistry and solid state physics. In the case of the five-electron species, the availability of the new data for a wide range of the confinement strengths ω allows for confirmation and generalization of the previously reached conclusions concerning the performance of the presently known approximations for the electron-electron repulsion energy in terms of the 1-matrix that are at heart of the density matrix functional theory (DMFT). On the other hand, the properties of the three low-lying states of the six-electron harmonium atom, computed at ω = 500 and ω = 1000, uncover deficiencies of the 1-matrix functionals not revealed by previous studies. In general, the previously published assessment of the present implementations of DMFT being of poor accuracy is found to hold. Extending the present work to harmonically confined systems with even more electrons is most likely counterproductive as the steep increase in computational cost required to maintain sufficient accuracy of the calculated properties is not expected to be matched by the benefits of additional information gathered from the resulting benchmarks.
Hierarchical low-rank approximation for high dimensional approximation
Nouy, Anthony
2016-01-01
Tensor methods are among the most prominent tools for the numerical solution of high-dimensional problems where functions of multiple variables have to be approximated. Such high-dimensional approximation problems naturally arise in stochastic analysis and uncertainty quantification. In many practical situations, the approximation of high-dimensional functions is made computationally tractable by using rank-structured approximations. In this talk, we present algorithms for the approximation in hierarchical tensor format using statistical methods. Sparse representations in a given tensor format are obtained with adaptive or convex relaxation methods, with a selection of parameters using crossvalidation methods.
Hierarchical low-rank approximation for high dimensional approximation
Nouy, Anthony
2016-01-07
Tensor methods are among the most prominent tools for the numerical solution of high-dimensional problems where functions of multiple variables have to be approximated. Such high-dimensional approximation problems naturally arise in stochastic analysis and uncertainty quantification. In many practical situations, the approximation of high-dimensional functions is made computationally tractable by using rank-structured approximations. In this talk, we present algorithms for the approximation in hierarchical tensor format using statistical methods. Sparse representations in a given tensor format are obtained with adaptive or convex relaxation methods, with a selection of parameters using crossvalidation methods.
Reliable Function Approximation and Estimation
2016-08-16
compressed sensing results to a wide class of infinite -dimensional problems. We discuss four key application domains for the methods developed in this... infinite -dimensional problems. We discuss four key findings arising from this project, as related to uncertainty quantification, image processing, matrix...compressed sensing results to a wide class of infinite -dimensional problems. We discuss four key application domains for the methods developed in this project
Directory of Open Access Journals (Sweden)
Seung Oh Lee
2013-10-01
Full Text Available Collection and investigation of flood information are essential to understand the nature of floods, but this has proved difficult in data-poor environments, or in developing or under-developed countries due to economic and technological limitations. The development of remote sensing data, GIS, and modeling techniques have, therefore, proved to be useful tools in the analysis of the nature of floods. Accordingly, this study attempts to estimate a flood discharge using the generalized likelihood uncertainty estimation (GLUE methodology and a 1D hydraulic model, with remote sensing data and topographic data, under the assumed condition that there is no gauge station in the Missouri river, Nebraska, and Wabash River, Indiana, in the United States. The results show that the use of Landsat leads to a better discharge approximation on a large-scale reach than on a small-scale. Discharge approximation using the GLUE depended on the selection of likelihood measures. Consideration of physical conditions in study reaches could, therefore, contribute to an appropriate selection of informal likely measurements. The river discharge assessed by using Landsat image and the GLUE Methodology could be useful in supplementing flood information for flood risk management at a planning level in ungauged basins. However, it should be noted that this approach to the real-time application might be difficult due to the GLUE procedure.
Exact constants in approximation theory
Korneichuk, N
1991-01-01
This book is intended as a self-contained introduction for non-specialists, or as a reference work for experts, to the particular area of approximation theory that is concerned with exact constants. The results apply mainly to extremal problems in approximation theory, which in turn are closely related to numerical analysis and optimization. The book encompasses a wide range of questions and problems: best approximation by polynomials and splines; linear approximation methods, such as spline-approximation; optimal reconstruction of functions and linear functionals. Many of the results are base
Hutter, Jürg
2003-03-01
An efficient formulation of time-dependent linear response density functional theory for the use within the plane wave basis set framework is presented. The method avoids the transformation of the Kohn-Sham matrix into the canonical basis and references virtual orbitals only through a projection operator. Using a Lagrangian formulation nuclear derivatives of excited state energies within the Tamm-Dancoff approximation are derived. The algorithms were implemented into a pseudo potential/plane wave code and applied to the calculation of adiabatic excitation energies, optimized geometries and vibrational frequencies of three low lying states of formaldehyde. An overall good agreement with other time-dependent density functional calculations, multireference configuration interaction calculations and experimental data was found.
Garza, Alejandro J.; Bulik, Ireneusz W.; Alencar, Ana G. Sousa; Sun, Jianwei; Perdew, John P.; Scuseria, Gustavo E.
2016-04-01
Contrary to standard coupled cluster doubles (CCD) and Brueckner doubles (BD), singlet-paired analogues of CCD and BD (denoted here as CCD0 and BD0) do not break down when static correlation is present, but neglect substantial amounts of dynamic correlation. In fact, CCD0 and BD0 do not account for any contributions from multielectron excitations involving only same-spin electrons at all. We exploit this feature to add - without introducing double counting, self-interaction, or increase in cost - the missing correlation to these methods via meta-GGA (generalised gradient approximation) density functionals (Tao-Perdew-Staroverov-Scuseria and strongly constrained and appropriately normed). Furthermore, we improve upon these CCD0+DFT blends by invoking range separation: the short- and long-range correlations absent in CCD0/BD0 are evaluated with density functional theory and the direct random phase approximation, respectively. This corrects the description of long-range van der Waals forces. Comprehensive benchmarking shows that the combinations presented here are very accurate for weakly correlated systems, while also providing a reasonable description of strongly correlated problems without resorting to symmetry breaking.
Diophantine approximation and badly approximable sets
DEFF Research Database (Denmark)
Kristensen, S.; Thorn, R.; Velani, S.
2006-01-01
. The classical set Bad of `badly approximable' numbers in the theory of Diophantine approximation falls within our framework as do the sets Bad(i,j) of simultaneously badly approximable numbers. Under various natural conditions we prove that the badly approximable subsets of Omega have full Hausdorff dimension...
Strategic approach to outsourcing the research and development function
Firend, A.R
2010-01-01
This paper proposes an approach for outsourcing the R&D function. This model is to serve as a strategic approach to outsourcing that considers number of elements with strategic competitive advantage as an ultimate objective. This paper suggest that outsourcing research and development should be planed and conducted from a strategic standpoint and have positive impact on organizational competitive position by incorporating it into the overall\\ud strategy of the organization to reduce the numbe...
A review of function modeling: Approaches and applications
Erden, M.S.; Komoto, H.; Van Beek, T.J.; D'Amelio, V.; Echavarria, E.; Tomiyama, T.
2008-01-01
This work is aimed at establishing a common frame and understanding of function modeling (FM) for our ongoing research activities. A comparative review of the literature is performed to grasp the various FM approaches with their commonalities and differences. The relations of FM with the research fields of artificial intelligence, design theory, and maintenance are discussed. In this discussion the goals are to highlight the features of various classical approaches in relation to FM, to delin...
Wavelet approach to accelerator problems. 3: Melnikov functions and symplectic topology
International Nuclear Information System (INIS)
Fedorova, A.; Zeitlin, M.; Parsa, Z.
1997-05-01
This is the third part of a series of talks in which the authors present applications of methods of wavelet analysis to polynomial approximations for a number of accelerator physics problems. They consider the generalization of the variational wavelet approach to nonlinear polynomial problems to the case of Hamiltonian systems for which they need to preserve underlying symplectic or Poissonian or quasicomplex structures in any type of calculations. They use the approach for the problem of explicit calculations of Arnold-Weinstein curves via Floer variational approach from symplectic topology. The loop solutions are parameterized by the solutions of reduced algebraical problem--matrix Quadratic Mirror Filters equations. Also they consider wavelet approach to the calculations of Melnikov functions in the theory of homoclinic chaos in perturbed Hamiltonian systems
Directory of Open Access Journals (Sweden)
KUDRYAVTSEV Pavel Gennadievich
2015-02-01
Full Text Available The paper deals with possibilities to use quasi-homogenous approximation for discription of properties of dispersed systems. The authors applied statistical polymer method based on consideration of average structures of all possible macromolecules of the same weight. The equiations which allow evaluating many additive parameters of macromolecules and the systems with them were deduced. Statistical polymer method makes it possible to model branched, cross-linked macromolecules and the systems with them which are in equilibrium or non-equilibrium state. Fractal analysis of statistical polymer allows modeling different types of random fractal and other objects examined with the mehods of fractal theory. The method of fractal polymer can be also applied not only to polymers but also to composites, gels, associates in polar liquids and other packaged systems. There is also a description of the states of colloid solutions of silica oxide from the point of view of statistical physics. This approach is based on the idea that colloid solution of silica dioxide – sol of silica dioxide – consists of enormous number of interacting particles which are always in move. The paper is devoted to the research of ideal system of colliding but not interacting particles of sol. The analysis of behavior of silica sol was performed according to distribution Maxwell-Boltzmann and free path length was calculated. Using this data the number of the particles which can overcome the potential barrier in collision was calculated. To model kinetics of sol-gel transition different approaches were studied.
Cumulant approach to dynamical correlation functions at finite temperatures
International Nuclear Information System (INIS)
Tran Minhtien.
1993-11-01
A new theoretical approach, based on the introduction of cumulants, to calculate thermodynamic averages and dynamical correlation functions at finite temperatures is developed. The method is formulated in Liouville instead of Hilbert space and can be applied to operators which do not require to satisfy fermion or boson commutation relations. The application of the partitioning and projection methods for the dynamical correlation functions is discussed. The present method can be applied to weakly as well as to strongly correlated systems. (author). 9 refs
Pediatrician's knowledge on the approach of functional constipation
Vieira, Mario C.; Negrelle, Isadora Carolina Krueger; Webber, Karla Ulaf; Gosdal, Marjorie; Truppel, Sabine Krüger; Kusma, Solena Ziemer
2016-01-01
Abstract Objective: To evaluate the pediatrician's knowledge regarding the diagnostic and therapeutic approach of childhood functional constipation. Methods: A descriptive cross-sectional study was performed with the application of a self-administered questionnaire concerning a hypothetical clinical case of childhood functional constipation with fecal incontinence to physicians (n=297) randomly interviewed at the 36th Brazilian Congress of Pediatrics in 2013. Results: The majority of the p...
A Novel Synchronization-Based Approach for Functional Connectivity Analysis
Directory of Open Access Journals (Sweden)
Angela Lombardi
2017-01-01
Full Text Available Complex network analysis has become a gold standard to investigate functional connectivity in the human brain. Popular approaches for quantifying functional coupling between fMRI time series are linear zero-lag correlation methods; however, they might reveal only partial aspects of the functional links between brain areas. In this work, we propose a novel approach for assessing functional coupling between fMRI time series and constructing functional brain networks. A phase space framework is used to map couples of signals exploiting their cross recurrence plots (CRPs to compare the trajectories of the interacting systems. A synchronization metric is extracted from the CRP to assess the coupling behavior of the time series. Since the functional communities of a healthy population are expected to be highly consistent for the same task, we defined functional networks of task-related fMRI data of a cohort of healthy subjects and applied a modularity algorithm in order to determine the community structures of the networks. The within-group similarity of communities is evaluated to verify whether such new metric is robust enough against noise. The synchronization metric is also compared with Pearson’s correlation coefficient and the detected communities seem to better reflect the functional brain organization during the specific task.
A new approach to stochastic transport via the functional Volterra expansion
International Nuclear Information System (INIS)
Ziya Akcasu, A.; Corngold, N.
2005-01-01
In this paper we present a new algorithm (FDA) for the calculation of the mean and the variance of the flux in stochastic transport when the transport equation contains a spatially random parameter θ(r), such as the density of the medium. The approach is based on the renormalized functional Volterra expansion of the flux around its mean. The attractive feature of the approach is that it explicitly displays the functional dependence of the flux on the products of θ(r i ), and hence enables one to take ensemble averages directly to calculate the moments of the flux in terms of the correlation functions of the underlying random process. The renormalized deterministic transport equation for the mean flux has been obtained to the second order in θ(r), and a functional relationship between the variance and the mean flux has been derived to calculate the variance to this order. The feasibility and accuracy of FDA has been demonstrated in the case of stochastic diffusion, using the diffusion equation with a spatially random diffusion coefficient. The connection of FDA with the well-established approximation schemes in the field of stochastic linear differential equations, such as the Bourret approximation, developed by Van Kampen using cumulant expansion, and by Terwiel using projection operator formalism, which has recently been extended to stochastic transport by Corngold. We hope that FDA's potential will be explored numerically in more realistic applications of the stochastic transport. (authors)
Sequential approach to Colombeau's theory of generalized functions
International Nuclear Information System (INIS)
Todorov, T.D.
1987-07-01
J.F. Colombeau's generalized functions are constructed as equivalence classes of the elements of a specially chosen ultrapower of the class of the C ∞ -functions. The elements of this ultrapower are considered as sequences of C ∞ -functions, so in a sense, the sequential construction presented here refers to the original Colombeau theory just as, for example, the Mikusinski sequential approach to the distribution theory refers to the original Schwartz theory of distributions. The paper could be used as an elementary introduction to the Colombeau theory in which recently a solution was found to the problem of multiplication of Schwartz distributions. (author). Refs
The Feynman-Vernon Influence Functional Approach in QED
International Nuclear Information System (INIS)
Biryukov, Alexander; Shleenkov, Mark
2016-01-01
In the path integral approach we describe evolution of interacting electromagnetic and fermionic fields by the use of density matrix formalism. The equation for density matrix and transitions probability for fermionic field is obtained as average of electromagnetic field influence functional. We obtain a formula for electromagnetic field influence functional calculating for its various initial and final state. We derive electromagnetic field influence functional when its initial and final states are vacuum. We present Lagrangian for relativistic fermionic field under influence of electromagnetic field vacuum
A functional approach to emotion in autonomous systems.
Sanz, Ricardo; Hernández, Carlos; Gómez, Jaime; Hernando, Adolfo
2010-01-01
The construction of fully effective systems seems to pass through the proper exploitation of goal-centric self-evaluative capabilities that let the system teleologically self-manage. Emotions seem to provide this kind of functionality to biological systems and hence the interest in emotion for function sustainment in artificial systems performing in changing and uncertain environments; far beyond the media hullabaloo of displaying human-like emotion-laden faces in robots. This chapter provides a brief analysis of the scientific theories of emotion and presents an engineering approach for developing technology for robust autonomy by implementing functionality inspired in that of biological emotions.
A review of function modeling : Approaches and applications
Erden, M.S.; Komoto, H.; Van Beek, T.J.; D'Amelio, V.; Echavarria, E.; Tomiyama, T.
2008-01-01
This work is aimed at establishing a common frame and understanding of function modeling (FM) for our ongoing research activities. A comparative review of the literature is performed to grasp the various FM approaches with their commonalities and differences. The relations of FM with the research
Multicomponent and Dissipative Self-Assembly Approaches : Towards functional materials
Boekhoven, J.
2012-01-01
The use of self-assembly has proven to be a powerful approach to create smart and functional materials and has led to a vast variety of successful examples. However, the full potential of self-assembly has not been reached. Despite the number of successful artificial materials based on
Questionnaire of Executive Function for Dancers: An Ecological Approach
Wong, Alina; Rodriguez, Mabel; Quevedo, Liliana; de Cossio, Lourdes Fernandez; Borges, Ariel; Reyes, Alicia; Corral, Roberto; Blanco, Florentino; Alvarez, Miguel
2012-01-01
There is a current debate about the ecological validity of executive function (EF) tests. Consistent with the verisimilitude approach, this research proposes the Ballet Executive Scale (BES), a self-rating questionnaire that assimilates idiosyncratic executive behaviors of classical dance community. The BES was administrated to 149 adolescents,…
From Equation to Inequality Using a Function-Based Approach
Verikios, Petros; Farmaki, Vassiliki
2010-01-01
This article presents features of a qualitative research study concerning the teaching and learning of school algebra using a function-based approach in a grade 8 class, of 23 students, in 26 lessons, in a state school of Athens, in the school year 2003-2004. In this article, we are interested in the inequality concept and our aim is to…
Finite elements and approximation
Zienkiewicz, O C
2006-01-01
A powerful tool for the approximate solution of differential equations, the finite element is extensively used in industry and research. This book offers students of engineering and physics a comprehensive view of the principles involved, with numerous illustrative examples and exercises.Starting with continuum boundary value problems and the need for numerical discretization, the text examines finite difference methods, weighted residual methods in the context of continuous trial functions, and piecewise defined trial functions and the finite element method. Additional topics include higher o
Energy Technology Data Exchange (ETDEWEB)
Zuehlsdorff, T. J., E-mail: tjz21@cam.ac.uk; Payne, M. C. [Cavendish Laboratory, J. J. Thomson Avenue, Cambridge CB3 0HE (United Kingdom); Hine, N. D. M. [Department of Physics, University of Warwick, Coventry CV4 7AL (United Kingdom); Haynes, P. D. [Department of Materials, Imperial College London, Exhibition Road, London SW7 2AZ (United Kingdom); Department of Physics, Imperial College London, Exhibition Road, London SW7 2AZ (United Kingdom); Thomas Young Centre for Theory and Simulation of Materials, Imperial College London, Exhibition Road, London SW7 2AZ (United Kingdom)
2015-11-28
We present a solution of the full time-dependent density-functional theory (TDDFT) eigenvalue equation in the linear response formalism exhibiting a linear-scaling computational complexity with system size, without relying on the simplifying Tamm-Dancoff approximation (TDA). The implementation relies on representing the occupied and unoccupied subspaces with two different sets of in situ optimised localised functions, yielding a very compact and efficient representation of the transition density matrix of the excitation with the accuracy associated with a systematic basis set. The TDDFT eigenvalue equation is solved using a preconditioned conjugate gradient algorithm that is very memory-efficient. The algorithm is validated on a small test molecule and a good agreement with results obtained from standard quantum chemistry packages is found, with the preconditioner yielding a significant improvement in convergence rates. The method developed in this work is then used to reproduce experimental results of the absorption spectrum of bacteriochlorophyll in an organic solvent, where it is demonstrated that the TDA fails to reproduce the main features of the low energy spectrum, while the full TDDFT equation yields results in good qualitative agreement with experimental data. Furthermore, the need for explicitly including parts of the solvent into the TDDFT calculations is highlighted, making the treatment of large system sizes necessary that are well within reach of the capabilities of the algorithm introduced here. Finally, the linear-scaling properties of the algorithm are demonstrated by computing the lowest excitation energy of bacteriochlorophyll in solution. The largest systems considered in this work are of the same order of magnitude as a variety of widely studied pigment-protein complexes, opening up the possibility of studying their properties without having to resort to any semiclassical approximations to parts of the protein environment.
Prestack wavefield approximations
Alkhalifah, Tariq
2013-01-01
The double-square-root (DSR) relation offers a platform to perform prestack imaging using an extended single wavefield that honors the geometrical configuration between sources, receivers, and the image point, or in other words, prestack wavefields. Extrapolating such wavefields, nevertheless, suffers from limitations. Chief among them is the singularity associated with horizontally propagating waves. I have devised highly accurate approximations free of such singularities which are highly accurate. Specifically, I use Padé expansions with denominators given by a power series that is an order lower than that of the numerator, and thus, introduce a free variable to balance the series order and normalize the singularity. For the higher-order Padé approximation, the errors are negligible. Additional simplifications, like recasting the DSR formula as a function of scattering angle, allow for a singularity free form that is useful for constant-angle-gather imaging. A dynamic form of this DSR formula can be supported by kinematic evaluations of the scattering angle to provide efficient prestack wavefield construction. Applying a similar approximation to the dip angle yields an efficient 1D wave equation with the scattering and dip angles extracted from, for example, DSR ray tracing. Application to the complex Marmousi data set demonstrates that these approximations, although they may provide less than optimal results, allow for efficient and flexible implementations. © 2013 Society of Exploration Geophysicists.
Prestack wavefield approximations
Alkhalifah, Tariq
2013-09-01
The double-square-root (DSR) relation offers a platform to perform prestack imaging using an extended single wavefield that honors the geometrical configuration between sources, receivers, and the image point, or in other words, prestack wavefields. Extrapolating such wavefields, nevertheless, suffers from limitations. Chief among them is the singularity associated with horizontally propagating waves. I have devised highly accurate approximations free of such singularities which are highly accurate. Specifically, I use Padé expansions with denominators given by a power series that is an order lower than that of the numerator, and thus, introduce a free variable to balance the series order and normalize the singularity. For the higher-order Padé approximation, the errors are negligible. Additional simplifications, like recasting the DSR formula as a function of scattering angle, allow for a singularity free form that is useful for constant-angle-gather imaging. A dynamic form of this DSR formula can be supported by kinematic evaluations of the scattering angle to provide efficient prestack wavefield construction. Applying a similar approximation to the dip angle yields an efficient 1D wave equation with the scattering and dip angles extracted from, for example, DSR ray tracing. Application to the complex Marmousi data set demonstrates that these approximations, although they may provide less than optimal results, allow for efficient and flexible implementations. © 2013 Society of Exploration Geophysicists.
Roper, Ian P E; Besley, Nicholas A
2016-03-21
The simulation of X-ray emission spectra of transition metal complexes with time-dependent density functional theory (TDDFT) is investigated. X-ray emission spectra can be computed within TDDFT in conjunction with the Tamm-Dancoff approximation by using a reference determinant with a vacancy in the relevant core orbital, and these calculations can be performed using the frozen orbital approximation or with the relaxation of the orbitals of the intermediate core-ionised state included. Both standard exchange-correlation functionals and functionals specifically designed for X-ray emission spectroscopy are studied, and it is shown that the computed spectral band profiles are sensitive to the exchange-correlation functional used. The computed intensities of the spectral bands can be rationalised by considering the metal p orbital character of the valence molecular orbitals. To compute X-ray emission spectra with the correct energy scale allowing a direct comparison with experiment requires the relaxation of the core-ionised state to be included and the use of specifically designed functionals with increased amounts of Hartree-Fock exchange in conjunction with high quality basis sets. A range-corrected functional with increased Hartree-Fock exchange in the short range provides transition energies close to experiment and spectral band profiles that have a similar accuracy to those from standard functionals.
Prestack traveltime approximations
Alkhalifah, Tariq Ali
2011-01-01
Most prestack traveltime relations we tend work with are based on homogeneous (or semi-homogenous, possibly effective) media approximations. This includes the multi-focusing or double square-root (DSR) and the common reflection stack (CRS) equations. Using the DSR equation, I analyze the associated eikonal form in the general source-receiver domain. Like its wave-equation counterpart, it suffers from a critical singularity for horizontally traveling waves. As a result, I derive expansion based solutions of this eikonal based on polynomial expansions in terms of the reflection and dip angles in a generally inhomogenous background medium. These approximate solutions are free of singularities and can be used to estimate travetimes for small to moderate offsets (or reflection angles) in a generally inhomogeneous medium. A Marmousi example demonstrates the usefulness of the approach. © 2011 Society of Exploration Geophysicists.
An evolutionary computation approach to examine functional brain plasticity
Directory of Open Access Journals (Sweden)
Arnab eRoy
2016-04-01
Full Text Available One common research goal in systems neurosciences is to understand how the functional relationship between a pair of regions of interest (ROIs evolves over time. Examining neural connectivity in this way is well-suited for the study of developmental processes, learning, and even in recovery or treatment designs in response to injury. For most fMRI based studies, the strength of the functional relationship between two ROIs is defined as the correlation between the average signal representing each region. The drawback to this approach is that much information is lost due to averaging heterogeneous voxels, and therefore, the functional relationship between a ROI-pair that evolve at a spatial scale much finer than the ROIs remain undetected. To address this shortcoming, we introduce a novel evolutionary computation (EC based voxel-level procedure to examine functional plasticity between an investigator defined ROI-pair by simultaneously using subject-specific BOLD-fMRI data collected from two sessions seperated by finite duration of time. This data-driven procedure detects a sub-region composed of spatially connected voxels from each ROI (a so-called sub-regional-pair such that the pair shows a significant gain/loss of functional relationship strength across the two time points. The procedure is recursive and iteratively finds all statistically significant sub-regional-pairs within the ROIs. Using this approach, we examine functional plasticity between the default mode network (DMN and the executive control network (ECN during recovery from traumatic brain injury (TBI; the study includes 14 TBI and 12 healthy control subjects. We demonstrate that the EC based procedure is able to detect functional plasticity where a traditional averaging based approach fails. The subject-specific plasticity estimates obtained using the EC-procedure are highly consistent across multiple runs. Group-level analyses using these plasticity estimates showed an increase in
Approximate Bayesian computation.
Directory of Open Access Journals (Sweden)
Mikael Sunnåker
Full Text Available Approximate Bayesian computation (ABC constitutes a class of computational methods rooted in Bayesian statistics. In all model-based statistical inference, the likelihood function is of central importance, since it expresses the probability of the observed data under a particular statistical model, and thus quantifies the support data lend to particular values of parameters and to choices among different models. For simple models, an analytical formula for the likelihood function can typically be derived. However, for more complex models, an analytical formula might be elusive or the likelihood function might be computationally very costly to evaluate. ABC methods bypass the evaluation of the likelihood function. In this way, ABC methods widen the realm of models for which statistical inference can be considered. ABC methods are mathematically well-founded, but they inevitably make assumptions and approximations whose impact needs to be carefully assessed. Furthermore, the wider application domain of ABC exacerbates the challenges of parameter estimation and model selection. ABC has rapidly gained popularity over the last years and in particular for the analysis of complex problems arising in biological sciences (e.g., in population genetics, ecology, epidemiology, and systems biology.
Rebenda, Josef; Šmarda, Zdeněk
2017-07-01
In the paper an efficient semi-analytical approach based on the method of steps and the differential transformation is proposed for numerical approximation of solutions of functional differential models of delayed and neutral type on a finite interval of arbitrary length, including models with several constant delays. Algorithms for both commensurate and non-commensurate delays are described, applications are shown in examples. Validity and efficiency of the presented algorithms is compared with the variational iteration method, the Adomian decomposition method and the polynomial least squares method numerically. Matlab package DDE23 is used to produce reference numerical values.
Elements of a function analytic approach to probability.
Energy Technology Data Exchange (ETDEWEB)
Ghanem, Roger Georges (University of Southern California, Los Angeles, CA); Red-Horse, John Robert
2008-02-01
We first provide a detailed motivation for using probability theory as a mathematical context in which to analyze engineering and scientific systems that possess uncertainties. We then present introductory notes on the function analytic approach to probabilistic analysis, emphasizing the connections to various classical deterministic mathematical analysis elements. Lastly, we describe how to use the approach as a means to augment deterministic analysis methods in a particular Hilbert space context, and thus enable a rigorous framework for commingling deterministic and probabilistic analysis tools in an application setting.
Abelian Chern endash Simons theory. II. A functional integral approach
International Nuclear Information System (INIS)
Manoliu, M.
1998-01-01
Following Witten, [Commun. Math. Phys. 21, 351 endash 399 (1989)] we approach the Abelian quantum Chern endash Simons (CS) gauge theory from a Feynman functional integral point of view. We show that for 3-manifolds with and without a boundary the formal functional integral definitions lead to mathematically proper expressions that agree with the results from the rigorous construction [J. Math. Phys. 39, 170 endash 206 (1998)] of the Abelian CS topological quantum field theory via geometric quantization. copyright 1998 American Institute of Physics
International Nuclear Information System (INIS)
El Sawi, M.
1983-07-01
A simple approach employing properties of solutions of differential equations is adopted to derive an appropriate extension of the WKBJ method. Some of the earlier techniques that are commonly in use are unified, whereby the general approximate solution to a second-order homogeneous linear differential equation is presented in a standard form that is valid for all orders. In comparison to other methods, the present one is shown to be leading in the order of iteration, and thus possibly has the ability of accelerating the convergence of the solution. The method is also extended for the solution of inhomogeneous equations. (author)
Yuan, Shifei; Jiang, Lei; Yin, Chengliang; Wu, Hongjie; Zhang, Xi
2017-06-01
To guarantee the safety, high efficiency and long lifetime for lithium-ion battery, an advanced battery management system requires a physics-meaningful yet computationally efficient battery model. The pseudo-two dimensional (P2D) electrochemical model can provide physical information about the lithium concentration and potential distributions across the cell dimension. However, the extensive computation burden caused by the temporal and spatial discretization limits its real-time application. In this research, we propose a new simplified electrochemical model (SEM) by modifying the boundary conditions for electrolyte diffusion equations, which significantly facilitates the analytical solving process. Then to obtain a reduced order transfer function, the Padé approximation method is adopted to simplify the derived transcendental impedance solution. The proposed model with the reduced order transfer function can be briefly computable and preserve physical meanings through the presence of parameters such as the solid/electrolyte diffusion coefficients (Ds&De) and particle radius. The simulation illustrates that the proposed simplified model maintains high accuracy for electrolyte phase concentration (Ce) predictions, saying 0.8% and 0.24% modeling error respectively, when compared to the rigorous model under 1C-rate pulse charge/discharge and urban dynamometer driving schedule (UDDS) profiles. Meanwhile, this simplified model yields significantly reduced computational burden, which benefits its real-time application.
New approach to equipment quality evaluation method with distinct functions
Directory of Open Access Journals (Sweden)
Milisavljević Vladimir M.
2016-01-01
Full Text Available The paper presents new approach for improving method for quality evaluation and selection of equipment (devices and machinery by applying distinct functions. Quality evaluation and selection of devices and machinery is a multi-criteria problem which involves the consideration of numerous parameters of various origins. Original selection method with distinct functions is based on technical parameters with arbitrary evaluation of each parameter importance (weighting. Improvement of this method, presented in this paper, addresses the issue of weighting of parameters by using Delphi Method. Finally, two case studies are provided, which included quality evaluation of standard boilers for heating and evaluation of load-haul-dump (LHD machines, to demonstrate applicability of this approach. Analytical Hierarchical Process (AHP is used as a control method.
A minimalist functional group (MFG) approach for surrogate fuel formulation
Abdul Jameel, Abdul Gani; Naser, Nimal; Issayev, Gani; Touitou, Jamal; Ghosh, Manik Kumer; Emwas, Abdul-Hamid M.; Farooq, Aamir; Dooley, Stephen; Sarathy, Mani
2018-01-01
Surrogate fuel formulation has drawn significant interest due to its relevance towards understanding combustion properties of complex fuel mixtures. In this work, we present a novel approach for surrogate fuel formulation by matching target fuel functional groups, while minimizing the number of surrogate species. Five key functional groups; paraffinic CH, paraffinic CH, paraffinic CH, naphthenic CH–CH and aromatic C–CH groups in addition to structural information provided by the Branching Index (BI) were chosen as matching targets. Surrogates were developed for six FACE (Fuels for Advanced Combustion Engines) gasoline target fuels, namely FACE A, C, F, G, I and J. The five functional groups present in the fuels were qualitatively and quantitatively identified using high resolution H Nuclear Magnetic Resonance (NMR) spectroscopy. A further constraint was imposed in limiting the number of surrogate components to a maximum of two. This simplifies the process of surrogate formulation, facilitates surrogate testing, and significantly reduces the size and time involved in developing chemical kinetic models by reducing the number of thermochemical and kinetic parameters requiring estimation. Fewer species also reduces the computational expenses involved in simulating combustion in practical devices. The proposed surrogate formulation methodology is denoted as the Minimalist Functional Group (MFG) approach. The MFG surrogates were experimentally tested against their target fuels using Ignition Delay Times (IDT) measured in an Ignition Quality Tester (IQT), as specified by the standard ASTM D6890 methodology, and in a Rapid Compression Machine (RCM). Threshold Sooting Index (TSI) and Smoke Point (SP) measurements were also performed to determine the sooting propensities of the surrogates and target fuels. The results showed that MFG surrogates were able to reproduce the aforementioned combustion properties of the target FACE gasolines across a wide range of conditions
A minimalist functional group (MFG) approach for surrogate fuel formulation
Abdul Jameel, Abdul Gani
2018-03-20
Surrogate fuel formulation has drawn significant interest due to its relevance towards understanding combustion properties of complex fuel mixtures. In this work, we present a novel approach for surrogate fuel formulation by matching target fuel functional groups, while minimizing the number of surrogate species. Five key functional groups; paraffinic CH, paraffinic CH, paraffinic CH, naphthenic CH–CH and aromatic C–CH groups in addition to structural information provided by the Branching Index (BI) were chosen as matching targets. Surrogates were developed for six FACE (Fuels for Advanced Combustion Engines) gasoline target fuels, namely FACE A, C, F, G, I and J. The five functional groups present in the fuels were qualitatively and quantitatively identified using high resolution H Nuclear Magnetic Resonance (NMR) spectroscopy. A further constraint was imposed in limiting the number of surrogate components to a maximum of two. This simplifies the process of surrogate formulation, facilitates surrogate testing, and significantly reduces the size and time involved in developing chemical kinetic models by reducing the number of thermochemical and kinetic parameters requiring estimation. Fewer species also reduces the computational expenses involved in simulating combustion in practical devices. The proposed surrogate formulation methodology is denoted as the Minimalist Functional Group (MFG) approach. The MFG surrogates were experimentally tested against their target fuels using Ignition Delay Times (IDT) measured in an Ignition Quality Tester (IQT), as specified by the standard ASTM D6890 methodology, and in a Rapid Compression Machine (RCM). Threshold Sooting Index (TSI) and Smoke Point (SP) measurements were also performed to determine the sooting propensities of the surrogates and target fuels. The results showed that MFG surrogates were able to reproduce the aforementioned combustion properties of the target FACE gasolines across a wide range of conditions
Assessing Cognitive Function in Older Adults Using a Videoconference Approach
Teresa Costa Castanho; Liliana Amorim; Pedro Silva Moreira; José Mariz; Joana Almeida Palha; Nuno Sousa; Nadine Correia Santos
2016-01-01
Background: The use of communication technologies is an emerging trend in healthcare and research. Despite efficient, reliable and accurate neuropsychological batteries to evaluate cognitive performance in-person, more diverse and less expensive and time consuming solutions are needed. Here we conducted a pilot study to determine the applicability of a videoconference (VC, Skype (R)) approach to assess cognitive function in older adults, using The Telephone Interview for Cognitive Status-Modi...
A functional data analysis approach for genetic association studies
Reimherr, Matthew; Nicolae, Dan
2014-01-01
We present a new method based on Functional Data Analysis (FDA) for detecting associations between one or more scalar covariates and a longitudinal response, while correcting for other variables. Our methods exploit the temporal structure of longitudinal data in ways that are otherwise difficult with a multivariate approach. Our procedure, from an FDA perspective, is a departure from more established methods in two key aspects. First, the raw longitudinal phenotypes are assembled into functio...
A zeta function approach to the semiclassical quantization of maps
International Nuclear Information System (INIS)
Smilansky, Uzi.
1993-11-01
The quantum analogue of an area preserving map on a compact phase space is a unitary (evolution) operator which can be represented by a matrix of dimension L∝ℎ -1 . The semiclassical theory for spectrum of the evolution operator will be reviewed with special emphasize on developing a dynamical zeta function approach, similar to the one introduced recently for a semiclassical quantization of hamiltonian systems. (author)
Magnetic Resonance and Brain Function. Approaches from Physics
International Nuclear Information System (INIS)
Maraviglia, B.
1999-01-01
In the last decade of this millennium, while, on the one hand, the international scientific community has focused with increasing endeavour on the research about the great unknown of the mechanism and the pathologies of the human brain, on the other hand, the NMR community has achieved some important results, which should widely affect, in the future, the possibility of understanding the function and disfunction of the human brain. In the early 1980's, the beginning of the application of Magnetic Resonance Imaging (MRI) to the morphological study of the brain in vivo, has played an extraordinary role, which, since then, placed MRI in a leading position among the methodologies used for investigation and diagnostics of the Central Nervous System. In the 1990s, the objective of finding new means, based on MRI, capable of giving functional and metabolic information, with the highest possible space resolution, drove the scientists towards different approaches. Among these, the first one to generate a breakthrough in the localization of specific cerebral functions was the Blood Oxygen Level Development (BOLD) MRI. A very wide range of applications followed the discovery of BOLD imaging. Still, this method gives an indirect information of the localization of functions, via the variation of oxygen release and deoxyhemoglobin formation. Of course, a high-resolution spatial distribution of the metabolites, crucial to brain function, would give a deeper insight into the occurring processes. This finality is aimed at by the Double Magnetic Resonance methods, which are developing new procedures able to detect some metabolites with increasing sensitivity and resolution. A third new promising approach to functional MRI should derive from the use of hyperpolarized, opens a series of potential applications to the study of brain function
Functional Foods and Lifestyle Approaches for Diabetes Prevention and Management
Directory of Open Access Journals (Sweden)
Ahmad Alkhatib
2017-12-01
Full Text Available Functional foods contain biologically active ingredients associated with physiological health benefits for preventing and managing chronic diseases, such as type 2 diabetes mellitus (T2DM. A regular consumption of functional foods may be associated with enhanced anti-oxidant, anti-inflammatory, insulin sensitivity, and anti-cholesterol functions, which are considered integral to prevent and manage T2DM. Components of the Mediterranean diet (MD—such as fruits, vegetables, oily fish, olive oil, and tree nuts—serve as a model for functional foods based on their natural contents of nutraceuticals, including polyphenols, terpenoids, flavonoids, alkaloids, sterols, pigments, and unsaturated fatty acids. Polyphenols within MD and polyphenol-rich herbs—such as coffee, green tea, black tea, and yerba maté—have shown clinically-meaningful benefits on metabolic and microvascular activities, cholesterol and fasting glucose lowering, and anti-inflammation and anti-oxidation in high-risk and T2DM patients. However, combining exercise with functional food consumption can trigger and augment several metabolic and cardiovascular protective benefits, but it is under-investigated in people with T2DM and bariatric surgery patients. Detecting functional food benefits can now rely on an “omics” biological profiling of individuals’ molecular, genetics, transcriptomics, proteomics, and metabolomics, but is under-investigated in multi-component interventions. A personalized approach for preventing and managing T2DM should consider biological and behavioral models, and embed nutrition education as part of lifestyle diabetes prevention studies. Functional foods may provide additional benefits in such an approach.
A probabilistic approach to delineating functional brain regions
DEFF Research Database (Denmark)
Kalbitzer, Jan; Svarer, Claus; Frokjaer, Vibe G
2009-01-01
The purpose of this study was to develop a reliable observer-independent approach to delineating volumes of interest (VOIs) for functional brain regions that are not identifiable on structural MR images. The case is made for the raphe nuclei, a collection of nuclei situated in the brain stem known...... to be densely packed with serotonin transporters (5-hydroxytryptaminic [5-HTT] system). METHODS: A template set for the raphe nuclei, based on their high content of 5-HTT as visualized in parametric (11)C-labeled 3-amino-4-(2-dimethylaminomethyl-phenylsulfanyl)-benzonitrile PET images, was created for 10...... healthy subjects. The templates were subsequently included in the region sets used in a previously published automatic MRI-based approach to create an observer- and activity-independent probabilistic VOI map. The probabilistic map approach was tested in a different group of 10 subjects and compared...
Fuzzy set approach to quality function deployment: An investigation
Masud, Abu S. M.
1992-01-01
The final report of the 1992 NASA/ASEE Summer Faculty Fellowship at the Space Exploration Initiative Office (SEIO) in Langley Research Center is presented. Quality Function Deployment (QFD) is a process, focused on facilitating the integration of the customer's voice in the design and development of a product or service. Various input, in the form of judgements and evaluations, are required during the QFD analyses. All the input variables in these analyses are treated as numeric variables. The purpose of the research was to investigate how QFD analyses can be performed when some or all of the input variables are treated as linguistic variables with values expressed as fuzzy numbers. The reason for this consideration is that human judgement, perception, and cognition are often ambiguous and are better represented as fuzzy numbers. Two approaches for using fuzzy sets in QFD have been proposed. In both cases, all the input variables are considered as linguistic variables with values indicated as linguistic expressions. These expressions are then converted to fuzzy numbers. The difference between the two approaches is due to how the QFD computations are performed with these fuzzy numbers. In Approach 1, the fuzzy numbers are first converted to their equivalent crisp scores and then the QFD computations are performed using these crisp scores. As a result, the output of this approach are crisp numbers, similar to those in traditional QFD. In Approach 2, all the QFD computations are performed with the fuzzy numbers and the output are fuzzy numbers also. Both the approaches have been explained with the help of illustrative examples of QFD application. Approach 2 has also been applied in a QFD application exercise in SEIO, involving a 'mini moon rover' design. The mini moon rover is a proposed tele-operated vehicle that will traverse and perform various tasks, including autonomous operations, on the moon surface. The output of the moon rover application exercise is a
How do companies envisage the future? Functional foresight approaches
Directory of Open Access Journals (Sweden)
Kononiuk Anna
2017-12-01
Full Text Available The main aim of the paper is to present the synthesis of the results of methodological analysis conducted on examples of foresight projects executed in chosen companies representing four companies type: small and medium-sized enterprise (SME, nonprofit- organization, international corporations and consulting companies as well as to posit functional approach for the implementation of foresight research within organizations. The empirical part of the study is based on the qualitative approach. A multiple case study methodology is employed. The research objects are sixteen companies experienced in foresight research. The first part of the paper gives an overview of definitions of corporate foresight and the analysis of background that have influence on the conducting of foresight in large multinational companies on one side and SMEs on the other side. In the field of the theory of foresight research, the study demonstrates that there are different motivations for foresight introduction as well as different organizational structure of teams conducting the activities and the approaches that they use. In the practical perspective, the study and a detailed functional foresight approach proposed by authors could be valuable for SMEs who consider implementing foresight research into their strategic planning processes.
The quasilocalized charge approximation
International Nuclear Information System (INIS)
Kalman, G J; Golden, K I; Donko, Z; Hartmann, P
2005-01-01
The quasilocalized charge approximation (QLCA) has been used for some time as a formalism for the calculation of the dielectric response and for determining the collective mode dispersion in strongly coupled Coulomb and Yukawa liquids. The approach is based on a microscopic model in which the charges are quasilocalized on a short-time scale in local potential fluctuations. We review the conceptual basis and theoretical structure of the QLC approach and together with recent results from molecular dynamics simulations that corroborate and quantify the theoretical concepts. We also summarize the major applications of the QLCA to various physical systems, combined with the corresponding results of the molecular dynamics simulations and point out the general agreement and instances of disagreement between the two
Polynomial approximation on polytopes
Totik, Vilmos
2014-01-01
Polynomial approximation on convex polytopes in \\mathbf{R}^d is considered in uniform and L^p-norms. For an appropriate modulus of smoothness matching direct and converse estimates are proven. In the L^p-case so called strong direct and converse results are also verified. The equivalence of the moduli of smoothness with an appropriate K-functional follows as a consequence. The results solve a problem that was left open since the mid 1980s when some of the present findings were established for special, so-called simple polytopes.
A multifaceted approach to maximize erectile function and vascular health.
Meldrum, David R; Gambone, Joseph C; Morris, Marge A; Ignarro, Louis J
2010-12-01
To review the role of various factors influencing vascular nitric oxide (NO) and cyclic GMP, and consequently, erectile function and vascular health. Pertinent publications are reviewed. Daily moderate exercise stimulates vascular NO production. Maintenance of normal body weight and waist/hip ratio allows NO stimulation by insulin. Decreased intake of fat, sugar, and simple carbohydrates rapidly converted to sugar reduces the adverse effects of fatty acids and sugar on endothelial NO production. Omega-3 fatty acids stimulate endothelial NO release. Antioxidants boost NO production and prevent NO breakdown. Folic acid, calcium, vitamin C, and vitamin E support the biochemical pathways leading to NO release. Cessation of smoking and avoidance of excessive alcohol preserve normal endothelial function. Moderate use of alcohol and certain proprietary supplements may favorably influence erectile and vascular function. Treatment of any remaining testosterone deficit will both increase erectile function and reduce any associated metabolic syndrome. After production of NO and cyclic GMP are improved, use of phosphodiesterase-5 inhibitors should result in greater success in treating remaining erectile dysfunction. Recent studies have also suggested positive effects of phosphodiesterase-5 inhibitors on vascular function. A multifaceted approach will maximize both erectile function and vascular health. Copyright © 2010 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.
Density functional approach for pairing in finite size systems
International Nuclear Information System (INIS)
Hupin, G.
2011-09-01
The combination of functional theory where the energy is written as a functional of the density, and the configuration mixing method, provides an efficient description of nuclear ground and excited state properties. The specific pathologies that have been recently observed, show the lack of a clear underlying justification associated to the breaking and the restoration of symmetries within density functional theory. This thesis focuses on alternative treatments of pairing correlations in finite many body systems that consider the breaking and the restoration of the particle number conservation. The energy is written as a functional of a projected quasi-particle vacuum and can be linked to the one obtained within the configuration mixing framework. This approach has been applied to make the projection either before or after the application of the variational principle. It is more flexible than the usual configuration mixing method since it can handle more general effective interactions than the latter. The application to the Krypton isotopes shows the feasibility and the efficiency of the method to describe pairing near closed shell nuclei. Following a parallel path, a theory where the energy is written as a functional of the occupation number and natural orbitals is proposed. The new functional is benchmarked in an exactly solvable model, the pairing Hamiltonian. The efficiency and the applicability of the new theory have been tested for various pairing strengths, single particle energy spectra and numbers of particles. (author)
Zeta-function approach to Casimir energy with singular potentials
International Nuclear Information System (INIS)
Khusnutdinov, Nail R.
2006-01-01
In the framework of zeta-function approach the Casimir energy for three simple model system: single delta potential, step function potential and three delta potentials are analyzed. It is shown that the energy contains contributions which are peculiar to the potentials. It is suggested to renormalize the energy using the condition that the energy of infinitely separated potentials is zero which corresponds to subtraction all terms of asymptotic expansion of zeta-function. The energy obtained in this way obeys all physically reasonable conditions. It is finite in the Dirichlet limit, and it may be attractive or repulsive depending on the strength of potential. The effective action is calculated, and it is shown that the surface contribution appears. The renormalization of the effective action is discussed
Some results in Diophantine approximation
DEFF Research Database (Denmark)
Pedersen, Steffen Højris
the basic concepts on which the papers build. Among other it introduces metric Diophantine approximation, Mahler’s approach on algebraic approximation, the Hausdorff measure, and properties of the formal Laurent series over Fq. The introduction ends with a discussion on Mahler’s problem when considered......This thesis consists of three papers in Diophantine approximation, a subbranch of number theory. Preceding these papers is an introduction to various aspects of Diophantine approximation and formal Laurent series over Fq and a summary of each of the three papers. The introduction introduces...
International Nuclear Information System (INIS)
Garcia-Aldea, David; Alvarellos, J. E.
2008-01-01
We propose a kinetic energy density functional scheme with nonlocal terms based on the von Weizsaecker functional, instead of the more traditional approach where the nonlocal terms have the structure of the Thomas-Fermi functional. The proposed functionals recover the exact kinetic energy and reproduce the linear response function of homogeneous electron systems. In order to assess their quality, we have tested the total kinetic energies as well as the kinetic energy density for atoms. The results show that these nonlocal functionals give as good results as the most sophisticated functionals in the literature. The proposed scheme for constructing the functionals means a step ahead in the field of fully nonlocal kinetic energy functionals, because they are capable of giving better local behavior than the semilocal functionals, yielding at the same time accurate results for total kinetic energies. Moreover, the functionals enjoy the possibility of being evaluated as a single integral in momentum space if an adequate reference density is defined, and then quasilinear scaling for the computational cost can be achieved
Rollout sampling approximate policy iteration
Dimitrakakis, C.; Lagoudakis, M.G.
2008-01-01
Several researchers have recently investigated the connection between reinforcement learning and classification. We are motivated by proposals of approximate policy iteration schemes without value functions, which focus on policy representation using classifiers and address policy learning as a
International Nuclear Information System (INIS)
Li, J H; Dai, X D; Wang, T L; Liu, B X
2007-01-01
We propose a two-parameter binomial truncation function for the second-moment approximation of the tight-binding (TB-SMA) interatomic potential and illustrate in detail the procedure of constructing the potentials for binary and ternary transition metal systems. For the ternary Ni-Hf-Ti system, the lattice constants, cohesion energies, elastic constants and bulk moduli of six binary compounds, i.e. L1 2 Ni 3 Hf, NiHf 3 , Ni 3 Ti, NiTi 3 , Hf 3 Ti and HfTi 3 , are firstly acquired by ab initio calculations and then employed to derive the binomial-truncated TB-SMA Ni-Hf-Ti potential. Applying the ab initio derived Ni-Hf-Ti potential, the lattice constants, cohesive energy, elastic constants and bulk moduli of another six binary compounds, i.e. D0 3 NiHf 3 , NiTi 3 HfTi 3 , and B2 NiHf, NiTi, HfTi, and two ternary compounds, i.e. C1 b NiHfTi, L2 1 Ni 2 HfTi, are calculated, respectively. It is found that, for the eight binary compounds studied, the calculated lattice constants and cohesion energies are in excellent agreement with those directly acquired from ab initio calculations and that the elastic constants and bulk moduli calculated from the potential are also qualitatively consistent with the results from ab initio calculations
International Nuclear Information System (INIS)
Yuste, Santos Bravo; Abad, Enrique
2011-01-01
We present an iterative method to obtain approximations to Bessel functions of the first kind J p (x) (p > -1) via the repeated application of an integral operator to an initial seed function f 0 (x). The class of seed functions f 0 (x) leading to sets of increasingly accurate approximations f n (x) is considerably large and includes any polynomial. When the operator is applied once to a polynomial of degree s, it yields a polynomial of degree s + 2, and so the iteration of this operator generates sets of increasingly better polynomial approximations of increasing degree. We focus on the set of polynomial approximations generated from the seed function f 0 (x) = 1. This set of polynomials is useful not only for the computation of J p (x) but also from a physical point of view, as it describes the long-time decay modes of certain fractional diffusion and diffusion-wave problems.
Correlation functions of the spin chains. Algebraic Bethe Ansatz approach
International Nuclear Information System (INIS)
Kitanine, N.
2007-09-01
Spin chains are the basic elements of integrable quantum models. These models have direct applications in condense matter theory, in statistical physics, in quantum optics, in field theory and even in string theory but they are also important because they enable us to solve, in an exact manner, non-perturbative phenomena that otherwise would stay unresolved. The method described in this work is based on the algebraic Bethe Ansatz. It is shown how this method can be used for the computation of null temperature correlation functions of the Heisenberg 1/2 spin chain. The important point of this approach is the solution of the inverse quantum problem given by the XXZ spin chain. This solution as well as a simple formulae for the scalar product of the Bethe states, have enabled us to get the most basic correlation functions under the form of multiple integrals. The formalism of multiple integrals open the way for asymptotic analysis for a few physical quantities like the probability of vacuum formation. It is worth noticing that this formalism can give exact results for two-point functions that are the most important correlation functions for applications. A relationship has been discovered between these multiple integrals and the sum of the form factors. The results have been extended to dynamical correlation functions. (A.C.)
A three-way approach for protein function classification.
Directory of Open Access Journals (Sweden)
Hafeez Ur Rehman
Full Text Available The knowledge of protein functions plays an essential role in understanding biological cells and has a significant impact on human life in areas such as personalized medicine, better crops and improved therapeutic interventions. Due to expense and inherent difficulty of biological experiments, intelligent methods are generally relied upon for automatic assignment of functions to proteins. The technological advancements in the field of biology are improving our understanding of biological processes and are regularly resulting in new features and characteristics that better describe the role of proteins. It is inevitable to neglect and overlook these anticipated features in designing more effective classification techniques. A key issue in this context, that is not being sufficiently addressed, is how to build effective classification models and approaches for protein function prediction by incorporating and taking advantage from the ever evolving biological information. In this article, we propose a three-way decision making approach which provides provisions for seeking and incorporating future information. We considered probabilistic rough sets based models such as Game-Theoretic Rough Sets (GTRS and Information-Theoretic Rough Sets (ITRS for inducing three-way decisions. An architecture of protein functions classification with probabilistic rough sets based three-way decisions is proposed and explained. Experiments are carried out on Saccharomyces cerevisiae species dataset obtained from Uniprot database with the corresponding functional classes extracted from the Gene Ontology (GO database. The results indicate that as the level of biological information increases, the number of deferred cases are reduced while maintaining similar level of accuracy.
Limitations of shallow nets approximation.
Lin, Shao-Bo
2017-10-01
In this paper, we aim at analyzing the approximation abilities of shallow networks in reproducing kernel Hilbert spaces (RKHSs). We prove that there is a probability measure such that the achievable lower bound for approximating by shallow nets can be realized for all functions in balls of reproducing kernel Hilbert space with high probability, which is different with the classical minimax approximation error estimates. This result together with the existing approximation results for deep nets shows the limitations for shallow nets and provides a theoretical explanation on why deep nets perform better than shallow nets. Copyright © 2017 Elsevier Ltd. All rights reserved.
Polymer density functional approach to efficient evaluation of path integrals
DEFF Research Database (Denmark)
Brukhno, Andrey; Vorontsov-Velyaminov, Pavel N.; Bohr, Henrik
2005-01-01
A polymer density functional theory (P-DFT) has been extended to the case of quantum statistics within the framework of Feynman path integrals. We start with the exact P-DFT formalism for an ideal open chain and adapt its efficient numerical solution to the case of a ring. We show that, similarly......, the path integral problem can, in principle, be solved exactly by making use of the two-particle pair correlation function (2p-PCF) for the ends of an open polymer, half of the original. This way the exact data for one-dimensional quantum harmonic oscillator are reproduced in a wide range of temperatures....... The exact solution is not, though, reachable in three dimensions (3D) because of a vast amount of storage required for 2p-PCF. In order to treat closed paths in 3D, we introduce a so-called "open ring" approximation which proves to be rather accurate in the limit of long chains. We also employ a simple self...
Dual Approach to the Study of Land Market Functioning
Directory of Open Access Journals (Sweden)
Liliya Oganesovna Oganesyan
2015-12-01
Full Text Available The article reveals the essence, the structural elements and features of the mechanism of functioning of the market of agricultural land. The authors present the supplementing idea on the structural dichotomy of the agricultural land market. In contrast to neoclassical approaches, it is proposed to explore the market based on its structural dichotomy – market property rights and market rights of management. In this context, the mechanism of functioning of agricultural lands market performs the function of a basic element in the system of land relations to ensure market circulation of agricultural land through alienation and assign full or partial rights of land ownership. The use of the institutional approach to the study of market structures justifies the dual nature of the mechanism of functioning of the market of agricultural land due to the fact that on the one hand, the market is slow and limited in the market space of the rare economic good or factor of production, and on the other hand, it is a dynamic institutional and economic system within which the specification of property rights to land is implemented. The structure of the mechanism of functioning and development of agricultural land market is considered as a system of interrelated and interacting elements of state regulation and market self-regulation, based on the principles of coordination and harmonization of personalized economic interests and market law of supply and demand. The combination of elements of market self-regulation and state regulation allows in practice to justify the choice of model combinations of stable and changing elements of the mechanism. This combination complies with the institutional conditions for the functioning of the market of agricultural land considering the dominance of regulated sustainable standards at the market of property rights and in the frames of informal institutions at the market of the management rights. The authors prove the
Bayesian Approach to Spectral Function Reconstruction for Euclidean Quantum Field Theories
Burnier, Yannis; Rothkopf, Alexander
2013-11-01
We present a novel approach to the inference of spectral functions from Euclidean time correlator data that makes close contact with modern Bayesian concepts. Our method differs significantly from the maximum entropy method (MEM). A new set of axioms is postulated for the prior probability, leading to an improved expression, which is devoid of the asymptotically flat directions present in the Shanon-Jaynes entropy. Hyperparameters are integrated out explicitly, liberating us from the Gaussian approximations underlying the evidence approach of the maximum entropy method. We present a realistic test of our method in the context of the nonperturbative extraction of the heavy quark potential. Based on hard-thermal-loop correlator mock data, we establish firm requirements in the number of data points and their accuracy for a successful extraction of the potential from lattice QCD. Finally we reinvestigate quenched lattice QCD correlators from a previous study and provide an improved potential estimation at T=2.33TC.
The Navier-Stokes equations an elementary functional analytic approach
Sohr, Hermann
2001-01-01
The primary objective of this monograph is to develop an elementary and self-contained approach to the mathematical theory of a viscous, incompressible fluid in a domain of the Euclidean space, described by the equations of Navier-Stokes. Moreover, the theory is presented for completely general domains, in particular, for arbitrary unbounded, nonsmooth domains. Therefore, restriction was necessary to space dimensions two and three, which are also the most significant from a physical point of view. For mathematical generality, however, the linearized theory is expounded for general dimensions higher than one. Although the functional analytic approach developed here is, in principle, known to specialists, the present book fills a gap in the literature providing a systematic treatment of a subject that has been documented until now only in fragments. The book is mainly directed to students familiar with basic tools in Hilbert and Banach spaces. However, for the readers’ convenience, some fundamental properties...
Sensorimotor integration for functional recovery and the Bobath approach.
Levin, Mindy F; Panturin, Elia
2011-04-01
Bobath therapy is used to treat patients with neurological disorders. Bobath practitioners use hands-on approaches to elicit and reestablish typical movement patterns through therapist-controlled sensorimotor experiences within the context of task accomplishment. One aspect of Bobath practice, the recovery of sensorimotor function, is reviewed within the framework of current motor control theories. We focus on the role of sensory information in movement production, the relationship between posture and movement and concepts related to motor recovery and compensation with respect to this therapeutic approach. We suggest that a major barrier to the evaluation of the therapeutic effectiveness of the Bobath concept is the lack of a unified framework for both experimental identification and treatment of neurological motor deficits. More conclusive analysis of therapeutic effectiveness requires the development of specific outcomes that measure movement quality.
Developmental Programming of Renal Function and Re-Programming Approaches.
Nüsken, Eva; Dötsch, Jörg; Weber, Lutz T; Nüsken, Kai-Dietrich
2018-01-01
Chronic kidney disease affects more than 10% of the population. Programming studies have examined the interrelationship between environmental factors in early life and differences in morbidity and mortality between individuals. A number of important principles has been identified, namely permanent structural modifications of organs and cells, long-lasting adjustments of endocrine regulatory circuits, as well as altered gene transcription. Risk factors include intrauterine deficiencies by disturbed placental function or maternal malnutrition, prematurity, intrauterine and postnatal stress, intrauterine and postnatal overnutrition, as well as dietary dysbalances in postnatal life. This mini-review discusses critical developmental periods and long-term sequelae of renal programming in humans and presents studies examining the underlying mechanisms as well as interventional approaches to "re-program" renal susceptibility toward disease. Clinical manifestations of programmed kidney disease include arterial hypertension, proteinuria, aggravation of inflammatory glomerular disease, and loss of kidney function. Nephron number, regulation of the renin-angiotensin-aldosterone system, renal sodium transport, vasomotor and endothelial function, myogenic response, and tubuloglomerular feedback have been identified as being vulnerable to environmental factors. Oxidative stress levels, metabolic pathways, including insulin, leptin, steroids, and arachidonic acid, DNA methylation, and histone configuration may be significantly altered by adverse environmental conditions. Studies on re-programming interventions focused on dietary or anti-oxidative approaches so far. Further studies that broaden our understanding of renal programming mechanisms are needed to ultimately develop preventive strategies. Targeted re-programming interventions in animal models focusing on known mechanisms will contribute to new concepts which finally will have to be translated to human application. Early
Developmental Programming of Renal Function and Re-Programming Approaches
Directory of Open Access Journals (Sweden)
Eva Nüsken
2018-02-01
Full Text Available Chronic kidney disease affects more than 10% of the population. Programming studies have examined the interrelationship between environmental factors in early life and differences in morbidity and mortality between individuals. A number of important principles has been identified, namely permanent structural modifications of organs and cells, long-lasting adjustments of endocrine regulatory circuits, as well as altered gene transcription. Risk factors include intrauterine deficiencies by disturbed placental function or maternal malnutrition, prematurity, intrauterine and postnatal stress, intrauterine and postnatal overnutrition, as well as dietary dysbalances in postnatal life. This mini-review discusses critical developmental periods and long-term sequelae of renal programming in humans and presents studies examining the underlying mechanisms as well as interventional approaches to “re-program” renal susceptibility toward disease. Clinical manifestations of programmed kidney disease include arterial hypertension, proteinuria, aggravation of inflammatory glomerular disease, and loss of kidney function. Nephron number, regulation of the renin–angiotensin–aldosterone system, renal sodium transport, vasomotor and endothelial function, myogenic response, and tubuloglomerular feedback have been identified as being vulnerable to environmental factors. Oxidative stress levels, metabolic pathways, including insulin, leptin, steroids, and arachidonic acid, DNA methylation, and histone configuration may be significantly altered by adverse environmental conditions. Studies on re-programming interventions focused on dietary or anti-oxidative approaches so far. Further studies that broaden our understanding of renal programming mechanisms are needed to ultimately develop preventive strategies. Targeted re-programming interventions in animal models focusing on known mechanisms will contribute to new concepts which finally will have to be translated
Developmental Programming of Renal Function and Re-Programming Approaches
Nüsken, Eva; Dötsch, Jörg; Weber, Lutz T.; Nüsken, Kai-Dietrich
2018-01-01
Chronic kidney disease affects more than 10% of the population. Programming studies have examined the interrelationship between environmental factors in early life and differences in morbidity and mortality between individuals. A number of important principles has been identified, namely permanent structural modifications of organs and cells, long-lasting adjustments of endocrine regulatory circuits, as well as altered gene transcription. Risk factors include intrauterine deficiencies by disturbed placental function or maternal malnutrition, prematurity, intrauterine and postnatal stress, intrauterine and postnatal overnutrition, as well as dietary dysbalances in postnatal life. This mini-review discusses critical developmental periods and long-term sequelae of renal programming in humans and presents studies examining the underlying mechanisms as well as interventional approaches to “re-program” renal susceptibility toward disease. Clinical manifestations of programmed kidney disease include arterial hypertension, proteinuria, aggravation of inflammatory glomerular disease, and loss of kidney function. Nephron number, regulation of the renin–angiotensin–aldosterone system, renal sodium transport, vasomotor and endothelial function, myogenic response, and tubuloglomerular feedback have been identified as being vulnerable to environmental factors. Oxidative stress levels, metabolic pathways, including insulin, leptin, steroids, and arachidonic acid, DNA methylation, and histone configuration may be significantly altered by adverse environmental conditions. Studies on re-programming interventions focused on dietary or anti-oxidative approaches so far. Further studies that broaden our understanding of renal programming mechanisms are needed to ultimately develop preventive strategies. Targeted re-programming interventions in animal models focusing on known mechanisms will contribute to new concepts which finally will have to be translated to human application
A Goal-Function Approach to Analysis of Control Situations
DEFF Research Database (Denmark)
Lind, Morten
2010-01-01
The concept of situations plays a central role in all theories of meaning and context. and serve to frame or group events and other occurrences into coherent meaningful wholes. Situations are typed, may be interconnected and organized into higher level structures. In operation of industrial...... processes situations should identify operational aspects relevant for control agent’s decision making in plant supervision and control. Control situations can be understood as recurrent and interconnected patterns of control with important implications for control and HMI design. Goal-Function approaches...
The fruits of a functional approach for psychological science.
Stewart, Ian
2016-02-01
The current paper introduces relational frame theory (RFT) as a functional contextual approach to complex human behaviour and examines how this theory has contributed to our understanding of several key phenomena in psychological science. I will first briefly outline the philosophical foundation of RFT and then examine its conceptual basis and core concepts. Thereafter, I provide an overview of the empirical findings and applications that RFT has stimulated in a number of key domains such as language development, linguistic generativity, rule-following, analogical reasoning, intelligence, theory of mind, psychopathology and implicit cognition. © 2015 International Union of Psychological Science.
Entanglement probabilities of polymers: a white noise functional approach
International Nuclear Information System (INIS)
Bernido, Christopher C; Carpio-Bernido, M Victoria
2003-01-01
The entanglement probabilities for a highly flexible polymer to wind n times around a straight polymer are evaluated using white noise analysis. To introduce the white noise functional approach, the one-dimensional random walk problem is taken as an example. The polymer entanglement scenario, viewed as a random walk on a plane, is then treated and the entanglement probabilities are obtained for a magnetic flux confined along the straight polymer, and a case where an entangled polymer is subjected to the potential V = f-dot(s)θ. In the absence of the magnetic flux and the potential V, the entanglement probabilities reduce to a result obtained by Wiegel
A Model-Based Approach to Constructing Music Similarity Functions
West, Kris; Lamere, Paul
2006-12-01
Several authors have presented systems that estimate the audio similarity of two pieces of music through the calculation of a distance metric, such as the Euclidean distance, between spectral features calculated from the audio, related to the timbre or pitch of the signal. These features can be augmented with other, temporally or rhythmically based features such as zero-crossing rates, beat histograms, or fluctuation patterns to form a more well-rounded music similarity function. It is our contention that perceptual or cultural labels, such as the genre, style, or emotion of the music, are also very important features in the perception of music. These labels help to define complex regions of similarity within the available feature spaces. We demonstrate a machine-learning-based approach to the construction of a similarity metric, which uses this contextual information to project the calculated features into an intermediate space where a music similarity function that incorporates some of the cultural information may be calculated.
The Use of Modeling Approach for Teaching Exponential Functions
Nunes, L. F.; Prates, D. B.; da Silva, J. M.
2017-12-01
This work presents a discussion related to the teaching and learning of mathematical contents related to the study of exponential functions in a freshman students group enrolled in the first semester of the Science and Technology Bachelor’s (STB of the Federal University of Jequitinhonha and Mucuri Valleys (UFVJM). As a contextualization tool strongly mentioned in the literature, the modelling approach was used as an educational teaching tool to produce contextualization in the teaching-learning process of exponential functions to these students. In this sense, were used some simple models elaborated with the GeoGebra software and, to have a qualitative evaluation of the investigation and the results, was used Didactic Engineering as a methodology research. As a consequence of this detailed research, some interesting details about the teaching and learning process were observed, discussed and described.
Approximation of the decay of fission and activation product mixtures
International Nuclear Information System (INIS)
Henderson, R.W.
1991-01-01
The decay of the exposure rate from a mixture of fission and activation products is a complex function of time. The exact solution of the problem involves the solution of more than 150 tenth order Bateman equations. An approximation of this function is required for the practical solution of problems involving multiple integrations of this function. Historically this has been a power function, or a series of power functions, of time. The approach selected here has been to approximate the decay with a sum of exponential functions. This produces a continuous, single valued function, that can be made to approximate the given decay scheme to any desired degree of closeness. Further, the integral of the sum is easily calculated over any period. 3 refs
Functional renormalization group approach to interacting three-dimensional Weyl semimetals
Sharma, Anand; Scammell, Arthur; Krieg, Jan; Kopietz, Peter
2018-03-01
We investigate the effect of long-range Coulomb interaction on the quasiparticle properties and the dielectric function of clean three-dimensional Weyl semimetals at zero temperature using a functional renormalization group (FRG) approach. The Coulomb interaction is represented via a bosonic Hubbard-Stratonovich field which couples to the fermionic density. We derive truncated FRG flow equations for the fermionic and bosonic self-energies and for the three-legged vertices with two fermionic and one bosonic external legs. We consider two different cutoff schemes—cutoff in fermionic or bosonic propagators—in order to calculate the renormalized quasiparticle velocity and the dielectric function for an arbitrary number of Weyl nodes and the interaction strength. If we approximate the dielectric function by its static limit, our results for the velocity and the dielectric function are in good agreement with that of A. A. Abrikosov and S. D. Beneslavskiĭ [Sov. Phys. JETP 32, 699 (1971)] exhibiting slowly varying logarithmic momentum dependence for small momenta. We extend their result for an arbitrary number of Weyl nodes and finite frequency by evaluating the renormalized velocity in the presence of dynamic screening and calculate the wave function renormalization.
Approach for partial derivatives of the J (ξ, β) function in respect to β
International Nuclear Information System (INIS)
Martinez, A.S.; Monteiro, M.A.M.
1989-01-01
An approximated method for the calculation of the J (ξ, β) function, and its partial derivatives in respect to β, is presented in this paper. The J (ξ, β) - function and its partial derivatives are frequently used in the resonance integrals calculations. The results obtained with the present approximated method are found to be in good agreement with benchmark results. (author) [pt
The Navier-Stokes equations an elementary functional analytic approach
Sohr, Hermann
2001-01-01
The primary objective of this monograph is to develop an elementary and self contained approach to the mathematical theory of a viscous incompressible fluid in a domain 0 of the Euclidean space ]Rn, described by the equations of Navier Stokes. The book is mainly directed to students familiar with basic functional analytic tools in Hilbert and Banach spaces. However, for readers' convenience, in the first two chapters we collect without proof some fundamental properties of Sobolev spaces, distributions, operators, etc. Another important objective is to formulate the theory for a completely general domain O. In particular, the theory applies to arbitrary unbounded, non-smooth domains. For this reason, in the nonlinear case, we have to restrict ourselves to space dimensions n = 2,3 that are also most significant from the physical point of view. For mathematical generality, we will develop the lin earized theory for all n 2 2. Although the functional-analytic approach developed here is, in principle, known ...
Weighted approximation with varying weight
Totik, Vilmos
1994-01-01
A new construction is given for approximating a logarithmic potential by a discrete one. This yields a new approach to approximation with weighted polynomials of the form w"n"(" "= uppercase)P"n"(" "= uppercase). The new technique settles several open problems, and it leads to a simple proof for the strong asymptotics on some L p(uppercase) extremal problems on the real line with exponential weights, which, for the case p=2, are equivalent to power- type asymptotics for the leading coefficients of the corresponding orthogonal polynomials. The method is also modified toyield (in a sense) uniformly good approximation on the whole support. This allows one to deduce strong asymptotics in some L p(uppercase) extremal problems with varying weights. Applications are given, relating to fast decreasing polynomials, asymptotic behavior of orthogonal polynomials and multipoint Pade approximation. The approach is potential-theoretic, but the text is self-contained.
Garcia-Seisdedos, Hector; Ibarra-Molero, Beatriz; Sanchez-Ruiz, Jose M
2012-01-01
Protein promiscuity is of considerable interest due its role in adaptive metabolic plasticity, its fundamental connection with molecular evolution and also because of its biotechnological applications. Current views on the relation between primary and promiscuous protein activities stem largely from laboratory evolution experiments aimed at increasing promiscuous activity levels. Here, on the other hand, we attempt to assess the main features of the simultaneous modulation of the primary and promiscuous functions during the course of natural evolution. The computational/experimental approach we propose for this task involves the following steps: a function-targeted, statistical coupling analysis of evolutionary data is used to determine a set of positions likely linked to the recruitment of a promiscuous activity for a new function; a combinatorial library of mutations on this set of positions is prepared and screened for both, the primary and the promiscuous activities; a partial-least-squares reconstruction of the full combinatorial space is carried out; finally, an approximation to the Pareto set of variants with optimal primary/promiscuous activities is derived. Application of the approach to the emergence of folding catalysis in thioredoxin scaffolds reveals an unanticipated scenario: diverse patterns of primary/promiscuous activity modulation are possible, including a moderate (but likely significant in a biological context) simultaneous enhancement of both activities. We show that this scenario can be most simply explained on the basis of the conformational diversity hypothesis, although alternative interpretations cannot be ruled out. Overall, the results reported may help clarify the mechanisms of the evolution of new functions. From a different viewpoint, the partial-least-squares-reconstruction/Pareto-set-prediction approach we have introduced provides the computational basis for an efficient directed-evolution protocol aimed at the simultaneous
Pediatrician's knowledge on the approach of functional constipation.
Vieira, Mario C; Negrelle, Isadora Carolina Krueger; Webber, Karla Ulaf; Gosdal, Marjorie; Truppel, Sabine Krüger; Kusma, Solena Ziemer
2016-12-01
To evaluate the pediatrician's knowledge regarding the diagnostic and therapeutic approach of childhood functional constipation. A descriptive cross-sectional study was performed with the application of a self-administered questionnaire concerning a hypothetical clinical case of childhood functional constipation with fecal incontinence to physicians (n=297) randomly interviewed at the 36th Brazilian Congress of Pediatrics in 2013. The majority of the participants were females, the mean age was 44.1 years, the mean time of professional practice was 18.8 years; 56.9% were Board Certified by the Brazilian Society of Pediatrics. Additional tests were ordered by 40.4%; including abdominal radiography (19.5%), barium enema (10.4%), laboratory tests (9.8%), abdominal ultrasound (6.7%), colonoscopy (2.4%), manometry and rectal biopsy (both 1.7%). The most common interventions included lactulose (26.6%), mineral oil (17.5%), polyethylene glycol (14.5%), fiber supplement (9.1%) and milk of magnesia (5.4%). Nutritional guidance (84.8%), fecal disimpaction (17.2%) and toilet training (19.5%) were also indicated. Our results show that pediatricians do not adhere to current recommendations for the management of childhood functional constipation, as unnecessary tests were ordered and the first-line treatment was not prescribed. Copyright © 2016. Publicado por Elsevier Editora Ltda.
Pediatrician's knowledge on the approach of functional constipation
Directory of Open Access Journals (Sweden)
Mario C. Vieira
Full Text Available Abstract Objective: To evaluate the pediatrician's knowledge regarding the diagnostic and therapeutic approach of childhood functional constipation. Methods: A descriptive cross-sectional study was performed with the application of a self-administered questionnaire concerning a hypothetical clinical case of childhood functional constipation with fecal incontinence to physicians (n=297 randomly interviewed at the 36th Brazilian Congress of Pediatrics in 2013. Results: The majority of the participants were females, the mean age was 44.1 years, the mean time of professional practice was 18.8 years; 56.9% were Board Certified by the Brazilian Society of Pediatrics. Additional tests were ordered by 40.4%; including abdominal radiography (19.5%, barium enema (10.4%, laboratory tests (9.8%, abdominal ultrasound (6.7%, colonoscopy (2.4%, manometry and rectal biopsy (both 1.7%. The most common interventions included lactulose (26.6%, mineral oil (17.5%, polyethylene glycol (14.5%, fiber supplement (9.1% and milk of magnesia (5.4%. Nutritional guidance (84.8%, fecal disimpaction (17.2% and toilet training (19.5% were also indicated. Conclusions: Our results show that pediatricians do not adhere to current recommendations for the management of childhood functional constipation, as unnecessary tests were ordered and the first-line treatment was not prescribed.
Directory of Open Access Journals (Sweden)
KUDRYAVTSEV Pavel Gennadievich
2015-08-01
Full Text Available The paper deals with possibilities to use quasi-homogenous approximation for description of properties of dispersed systems. The authors applied statistical polymer method based on consideration of average structures of all possible macromolecules of the same weight. The equations which allow evaluating many additive parameters of macromolecules and the systems with them were deduced. Statistical polymer method makes it possible to model branched, cross-linked macromolecules and the systems with them which are in equilibrium or non-equilibrium state. Fractal analysis of statistical polymer allows modeling different types of random fractal and other objects examined with the methods of fractal theory. The method of fractal polymer can be applied not only to polymers but also to composites, gels, associates in polar liquids and other packaged systems. There is also a description of the states of colloid solutions of silica oxide from the point of view of statistical physics. This approach is based on the idea that colloid solution of silica dioxide – sol of silica dioxide – consists of enormous number of interacting particles which are always in move. The paper is devoted to the research of ideal system of colliding but not interacting particles of sol. The analysis of behavior of silica sol was performed according to distribution Maxwell-Boltzmann and free path length was calculated. Using this data the number of the particles which can overcome the potential barrier in collision was calculated. To model kinetics of sol-gel transition different approaches were studied.
Robotic approaches for rehabilitation of hand function after stroke.
Lum, Peter S; Godfrey, Sasha B; Brokaw, Elizabeth B; Holley, Rahsaan J; Nichols, Diane
2012-11-01
The goal of this review was to discuss the impairments in hand function after stroke and present previous work on robot-assisted approaches to movement neurorehabilitation. Robotic devices offer a unique training environment that may enhance outcomes beyond what is possible with conventional means. Robots apply forces to the hand, allowing completion of movements while preventing inappropriate movement patterns. Evidence from the literature is emerging that certain characteristics of the human-robot interaction are preferable. In light of this evidence, the robotic hand devices that have undergone clinical testing are reviewed, highlighting the authors' work in this area. Finally, suggestions for future work are offered. The ability to deliver therapy doses far higher than what has been previously tested is a potentially key advantage of robotic devices that needs further exploration. In particular, more efforts are needed to develop highly motivating home-based devices, which can increase access to high doses of assisted movement therapy.
Wetting transitions: A functional renormalization-group approach
International Nuclear Information System (INIS)
Fisher, D.S.; Huse, D.A.
1985-01-01
A linear functional renormalization group is introduced as a framework in which to treat various wetting transitions of films on substrates. A unified treatment of the wetting transition in three dimensions with short-range interactions is given. The results of Brezin, Halperin, and Leibler in their three different regimes are reproduced along with new results on the multicritical behavior connecting the various regimes. In addition, the critical behavior as the coexistence curve is approached at complete wetting is analyzed. Wetting in the presence of long-range substrate-film interactions that fall off as power laws is also studied. The possible effects of the nonlinear terms in the renormalization group are examined briefly and it appears that they do not alter the critical behavior found using the truncated linear renormalization group
Recent molecular approaches to understanding astrocyte function in vivo
Directory of Open Access Journals (Sweden)
David eDavila
2013-12-01
Full Text Available Astrocytes are a predominant glial cell type in the nervous systems, and are becoming recognized as important mediators of normal brain function as well as neurodevelopmental, neurological, and neurodegenerative brain diseases. Although numerous potential mechanisms have been proposed to explain the role of astrocytes in the normal and diseased brain, research into the physiological relevance of these mechanisms in vivo is just beginning. In this review, we will summarize recent developments in innovative and powerful molecular approaches, including knockout mouse models, transgenic mouse models, and astrocyte-targeted gene transfer/expression, which have led to advances in understanding astrocyte biology in vivo that were heretofore inaccessible to experimentation. We will examine the recently improved understanding of the roles of astrocytes - with an emphasis on astrocyte signaling - in the context of both the healthy and diseased brain, discuss areas where the role of astrocytes remains debated, and suggest new research directions.
CLARM: An integrative approach for functional modules discovery
Salem, Saeed M.; Alroobi, Rami; Banitaan, Shadi; Seridi, Loqmane; Brewer, James E.; Aljarah, Ibrahim
2011-01-01
Functional module discovery aims to find well-connected subnetworks which can serve as candidate protein complexes. Advances in High-throughput proteomic technologies have enabled the collection of large amount of interaction data as well as gene expression data. We propose, CLARM, a clustering algorithm that integrates gene expression profiles and protein protein interaction network for biological modules discovery. The main premise is that by enriching the interaction network by adding interactions between genes which are highly co-expressed over a wide range of biological and environmental conditions, we can improve the quality of the discovered modules. Protein protein interactions, known protein complexes, and gene expression profiles for diverse environmental conditions from the yeast Saccharomyces cerevisiae were used for evaluate the biological significance of the reported modules. Our experiments show that the CLARM approach is competitive to wellestablished module discovery methods. Copyright © 2011 ACM.
Energy Technology Data Exchange (ETDEWEB)
Li, Minjing [School; Qian, Wei-jun [Pacific Northwest National Laboratory, Richland, Washington 99354, United States; Gao, Yuqian [Pacific Northwest National Laboratory, Richland, Washington 99354, United States; Shi, Liang [School; Liu, Chongxuan [Pacific Northwest National Laboratory, Richland, Washington 99354, United States; School
2017-09-28
The kinetics of biogeochemical processes in natural and engineered environmental systems are typically described using Monod-type or modified Monod-type models. These models rely on biomass as surrogates for functional enzymes in microbial community that catalyze biogeochemical reactions. A major challenge to apply such models is the difficulty to quantitatively measure functional biomass for constraining and validating the models. On the other hand, omics-based approaches have been increasingly used to characterize microbial community structure, functions, and metabolites. Here we proposed an enzyme-based model that can incorporate omics-data to link microbial community functions with biogeochemical process kinetics. The model treats enzymes as time-variable catalysts for biogeochemical reactions and applies biogeochemical reaction network to incorporate intermediate metabolites. The sequences of genes and proteins from metagenomes, as well as those from the UniProt database, were used for targeted enzyme quantification and to provide insights into the dynamic linkage among functional genes, enzymes, and metabolites that are necessary to be incorporated in the model. The application of the model was demonstrated using denitrification as an example by comparing model-simulated with measured functional enzymes, genes, denitrification substrates and intermediates
A Model-Based Approach to Constructing Music Similarity Functions
Directory of Open Access Journals (Sweden)
Lamere Paul
2007-01-01
Full Text Available Several authors have presented systems that estimate the audio similarity of two pieces of music through the calculation of a distance metric, such as the Euclidean distance, between spectral features calculated from the audio, related to the timbre or pitch of the signal. These features can be augmented with other, temporally or rhythmically based features such as zero-crossing rates, beat histograms, or fluctuation patterns to form a more well-rounded music similarity function. It is our contention that perceptual or cultural labels, such as the genre, style, or emotion of the music, are also very important features in the perception of music. These labels help to define complex regions of similarity within the available feature spaces. We demonstrate a machine-learning-based approach to the construction of a similarity metric, which uses this contextual information to project the calculated features into an intermediate space where a music similarity function that incorporates some of the cultural information may be calculated.
International Nuclear Information System (INIS)
Chen Changyuan; Sun Dongsheng; Lu Falin
2007-01-01
Using the exponential function transformation approach along with an approximation for the centrifugal potential, the radial Klein-Gordon equation with the vector and scalar Hulthen potential is transformed to a hypergeometric differential equation. The approximate analytical solutions of bound states are attained for different l. The analytical energy equation and the unnormalized radial wave functions expressed in terms of hypergeometric polynomials are given
Directory of Open Access Journals (Sweden)
A. KH. Alassafee
2017-11-01
Full Text Available The modified DebyeâEinstein approximation model is used to calculate nanoscale size-dependent values of Gruneisen parameters and lattice specific heat capacity for Si nanowires. All parameters forming the model, including Debye temperatures, bulk moduli, the lattice thermal expansion and the lattice volume, are calculated according to their nanoscale size dependence. Values for lattice volume Gruneisen parameters increase with the decrease of the nanowiresâ diameter, while all other parameters decrease. The nanosize dependence of lattice thermal parameters agree with other reported theoretical results. Keywords: Lattice specific heat capacity, Gruneisen parameter, DebyeâEinstein model, Si nanowires
Moin, Mazahar; Bakshi, Achala; Saha, Anusree; Dutta, Mouboni; Kirti, P B
2017-07-01
The epitome of any genome research is to identify all the existing genes in a genome and investigate their roles. Various techniques have been applied to unveil the functions either by silencing or over-expressing the genes by targeted expression or random mutagenesis. Rice is the most appropriate model crop for generating a mutant resource for functional genomic studies because of the availability of high-quality genome sequence and relatively smaller genome size. Rice has syntenic relationships with members of other cereals. Hence, characterization of functionally unknown genes in rice will possibly provide key genetic insights and can lead to comparative genomics involving other cereals. The current review attempts to discuss the available gain-of-function mutagenesis techniques for functional genomics, emphasizing the contemporary approach, activation tagging and alterations to this method for the enhancement of yield and productivity of rice. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.
Prestack traveltime approximations
Alkhalifah, Tariq Ali
2012-05-01
Many of the explicit prestack traveltime relations used in practice are based on homogeneous (or semi-homogenous, possibly effective) media approximations. This includes the multifocusing, based on the double square-root (DSR) equation, and the common reflection stack (CRS) approaches. Using the DSR equation, I constructed the associated eikonal form in the general source-receiver domain. Like its wave-equation counterpart, it suffers from a critical singularity for horizontally traveling waves. As a result, I recasted the eikonal in terms of the reflection angle, and thus, derived expansion based solutions of this eikonal in terms of the difference between the source and receiver velocities in a generally inhomogenous background medium. The zero-order term solution, corresponding to ignoring the lateral velocity variation in estimating the prestack part, is free of singularities and can be used to estimate traveltimes for small to moderate offsets (or reflection angles) in a generally inhomogeneous medium. The higher-order terms include limitations for horizontally traveling waves, however, we can readily enforce stability constraints to avoid such singularities. In fact, another expansion over reflection angle can help us avoid these singularities by requiring the source and receiver velocities to be different. On the other hand, expansions in terms of reflection angles result in singularity free equations. For a homogenous background medium, as a test, the solutions are reasonably accurate to large reflection and dip angles. A Marmousi example demonstrated the usefulness and versatility of the formulation. © 2012 Society of Exploration Geophysicists.
Approximate symmetries of Hamiltonians
Chubb, Christopher T.; Flammia, Steven T.
2017-08-01
We explore the relationship between approximate symmetries of a gapped Hamiltonian and the structure of its ground space. We start by considering approximate symmetry operators, defined as unitary operators whose commutators with the Hamiltonian have norms that are sufficiently small. We show that when approximate symmetry operators can be restricted to the ground space while approximately preserving certain mutual commutation relations. We generalize the Stone-von Neumann theorem to matrices that approximately satisfy the canonical (Heisenberg-Weyl-type) commutation relations and use this to show that approximate symmetry operators can certify the degeneracy of the ground space even though they only approximately form a group. Importantly, the notions of "approximate" and "small" are all independent of the dimension of the ambient Hilbert space and depend only on the degeneracy in the ground space. Our analysis additionally holds for any gapped band of sufficiently small width in the excited spectrum of the Hamiltonian, and we discuss applications of these ideas to topological quantum phases of matter and topological quantum error correcting codes. Finally, in our analysis, we also provide an exponential improvement upon bounds concerning the existence of shared approximate eigenvectors of approximately commuting operators under an added normality constraint, which may be of independent interest.
Faster exact Markovian probability functions for motif occurrences: a DFA-only approach.
Ribeca, Paolo; Raineri, Emanuele
2008-12-15
The computation of the statistical properties of motif occurrences has an obviously relevant application: patterns that are significantly over- or under-represented in genomes or proteins are interesting candidates for biological roles. However, the problem is computationally hard; as a result, virtually all the existing motif finders use fast but approximate scoring functions, in spite of the fact that they have been shown to produce systematically incorrect results. A few interesting exact approaches are known, but they are very slow and hence not practical in the case of realistic sequences. We give an exact solution, solely based on deterministic finite-state automata (DFA), to the problem of finding the whole relevant part of the probability distribution function of a simple-word motif in a homogeneous (biological) sequence. Out of that, the z-value can always be computed, while the P-value can be obtained either when it is not too extreme with respect to the number of floating-point digits available in the implementation, or when the number of pattern occurrences is moderately low. In particular, the time complexity of the algorithms for Markov models of moderate order (0 manage to obtain an algorithm which is both easily interpretable and efficient. This approach can be used for exact statistical studies of very long genomes and protein sequences, as we illustrate with some examples on the scale of the human genome.
Executive Function and Food Approach Behavior in Middle Childhood
Directory of Open Access Journals (Sweden)
Karoline eGroppe
2014-05-01
Full Text Available Executive function (EF has long been considered to be a unitary, domain-general cognitive ability. However, recent research suggests differentiating ‘hot’ affective and ‘cool’ cognitive aspects of EF. Yet, findings regarding this two-factor construct are still inconsistent. In particular, the development of this factor structure remains unclear and data on school-aged children is lacking. Furthermore, studies linking EF and overweight or obesity suggest that EF contributes to the regulation of eating behavior. So far, however, the links between EF and eating behavior have rarely been investigated in children and non-clinical populations.First, we examined whether EF can be divided into hot and cool factors or whether they actually correspond to a unitary construct in middle childhood. Second, we examined how hot and cool EF are associated with different eating styles that put children at risk of becoming overweight during development. Hot and cool EF were assessed experimentally in a non-clinical population of 1,657 elementary-school children (aged 6-11 years. The ‘food approach’ behavior was rated mainly via parent questionnaires.Findings indicate that hot EF is distinguishable from cool EF. However, only cool EF seems to represent a coherent functional entity, whereas hot EF does not seem to be a homogenous construct. This was true for a younger and an older subgroup of children. Furthermore, different EF components were correlated with eating styles, such as responsiveness to food, desire to drink, and restrained eating in girls but not in boys. This shows that lower levels of EF are not only seen in clinical populations of obese patients but are already associated with food approach styles in a normal population of elementary school-aged girls. Although the direction of effect still has to be clarified, results point to the possibility that EF constitutes a risk factor for eating styles contributing to the development of
Directory of Open Access Journals (Sweden)
Henrik Bjørn Nielsen
2007-08-01
Full Text Available The systematic comparison of transcriptional responses of organisms is a powerful tool in functional genomics. For example, mutants may be characterized by comparing their transcript profiles to those obtained in other experiments querying the effects on gene expression of many experimental factors including treatments, mutations and pathogen infections. Similarly, drugs may be discovered by the relationship between the transcript profiles effectuated or impacted by a candidate drug and by the target disease. The integration of such data enables systems biology to predict the interplay between experimental factors affecting a biological system. Unfortunately, direct comparisons of gene expression profiles obtained in independent, publicly available microarray experiments are typically compromised by substantial, experiment-specific biases. Here we suggest a novel yet conceptually simple approach for deriving 'Functional Association(s by Response Overlap' (FARO between microarray gene expression studies. The transcriptional response is defined by the set of differentially expressed genes independent from the magnitude or direction of the change. This approach overcomes the limited comparability between studies that is typical for methods that rely on correlation in gene expression. We apply FARO to a compendium of 242 diverse Arabidopsis microarray experimental factors, including phyto-hormones, stresses and pathogens, growth conditions/stages, tissue types and mutants. We also use FARO to confirm and further delineate the functions of Arabidopsis MAP kinase 4 in disease and stress responses. Furthermore, we find that a large, well-defined set of genes responds in opposing directions to different stress conditions and predict the effects of different stress combinations. This demonstrates the usefulness of our approach for exploiting public microarray data to derive biologically meaningful associations between experimental factors. Finally, our
Approximate Reanalysis in Topology Optimization
DEFF Research Database (Denmark)
Amir, Oded; Bendsøe, Martin P.; Sigmund, Ole
2009-01-01
In the nested approach to structural optimization, most of the computational effort is invested in the solution of the finite element analysis equations. In this study, the integration of an approximate reanalysis procedure into the framework of topology optimization of continuum structures...