NASA Astrophysics Data System (ADS)
Naumenko, Mikhail; Samarin, Viacheslav
2018-02-01
Modern parallel computing algorithm has been applied to the solution of the few-body problem. The approach is based on Feynman's continual integrals method implemented in C++ programming language using NVIDIA CUDA technology. A wide range of 3-body and 4-body bound systems has been considered including nuclei described as consisting of protons and neutrons (e.g., 3,4He) and nuclei described as consisting of clusters and nucleons (e.g., 6He). The correctness of the results was checked by the comparison with the exactly solvable 4-body oscillatory system and experimental data.
Algorithmic transformation of multi-loop master integrals to a canonical basis with CANONICA
NASA Astrophysics Data System (ADS)
Meyer, Christoph
2018-01-01
The integration of differential equations of Feynman integrals can be greatly facilitated by using a canonical basis. This paper presents the Mathematica package CANONICA, which implements a recently developed algorithm to automatize the transformation to a canonical basis. This represents the first publicly available implementation suitable for differential equations depending on multiple scales. In addition to the presentation of the package, this paper extends the description of some aspects of the algorithm, including a proof of the uniqueness of canonical forms up to constant transformations.
Temme, K; Osborne, T J; Vollbrecht, K G; Poulin, D; Verstraete, F
2011-03-03
The original motivation to build a quantum computer came from Feynman, who imagined a machine capable of simulating generic quantum mechanical systems--a task that is believed to be intractable for classical computers. Such a machine could have far-reaching applications in the simulation of many-body quantum physics in condensed-matter, chemical and high-energy systems. Part of Feynman's challenge was met by Lloyd, who showed how to approximately decompose the time evolution operator of interacting quantum particles into a short sequence of elementary gates, suitable for operation on a quantum computer. However, this left open the problem of how to simulate the equilibrium and static properties of quantum systems. This requires the preparation of ground and Gibbs states on a quantum computer. For classical systems, this problem is solved by the ubiquitous Metropolis algorithm, a method that has basically acquired a monopoly on the simulation of interacting particles. Here we demonstrate how to implement a quantum version of the Metropolis algorithm. This algorithm permits sampling directly from the eigenstates of the Hamiltonian, and thus evades the sign problem present in classical simulations. A small-scale implementation of this algorithm should be achievable with today's technology.
Smith, Kyle K G; Poulsen, Jens Aage; Nyman, Gunnar; Rossky, Peter J
2015-06-28
We develop two classes of quasi-classical dynamics that are shown to conserve the initial quantum ensemble when used in combination with the Feynman-Kleinert approximation of the density operator. These dynamics are used to improve the Feynman-Kleinert implementation of the classical Wigner approximation for the evaluation of quantum time correlation functions known as Feynman-Kleinert linearized path-integral. As shown, both classes of dynamics are able to recover the exact classical and high temperature limits of the quantum time correlation function, while a subset is able to recover the exact harmonic limit. A comparison of the approximate quantum time correlation functions obtained from both classes of dynamics is made with the exact results for the challenging model problems of the quartic and double-well potentials. It is found that these dynamics provide a great improvement over the classical Wigner approximation, in which purely classical dynamics are used. In a special case, our first method becomes identical to centroid molecular dynamics.
Simplifying Differential Equations for Multiscale Feynman Integrals beyond Multiple Polylogarithms.
Adams, Luise; Chaubey, Ekta; Weinzierl, Stefan
2017-04-07
In this Letter we exploit factorization properties of Picard-Fuchs operators to decouple differential equations for multiscale Feynman integrals. The algorithm reduces the differential equations to blocks of the size of the order of the irreducible factors of the Picard-Fuchs operator. As a side product, our method can be used to easily convert the differential equations for Feynman integrals which evaluate to multiple polylogarithms to an ϵ form.
Solving differential equations for Feynman integrals by expansions near singular points
NASA Astrophysics Data System (ADS)
Lee, Roman N.; Smirnov, Alexander V.; Smirnov, Vladimir A.
2018-03-01
We describe a strategy to solve differential equations for Feynman integrals by powers series expansions near singular points and to obtain high precision results for the corresponding master integrals. We consider Feynman integrals with two scales, i.e. non-trivially depending on one variable. The corresponding algorithm is oriented at situations where canonical form of the differential equations is impossible. We provide a computer code constructed with the help of our algorithm for a simple example of four-loop generalized sunset integrals with three equal non-zero masses and two zero masses. Our code gives values of the master integrals at any given point on the real axis with a required accuracy and a given order of expansion in the regularization parameter ɛ.
NASA Astrophysics Data System (ADS)
Volkov, Sergey
2017-11-01
This paper presents a new method of numerical computation of the mass-independent QED contributions to the electron anomalous magnetic moment which arise from Feynman graphs without closed electron loops. The method is based on a forestlike subtraction formula that removes all ultraviolet and infrared divergences in each Feynman graph before integration in Feynman-parametric space. The integration is performed by an importance sampling Monte-Carlo algorithm with the probability density function that is constructed for each Feynman graph individually. The method is fully automated at any order of the perturbation series. The results of applying the method to 2-loop, 3-loop, 4-loop Feynman graphs, and to some individual 5-loop graphs are presented, as well as the comparison of this method with other ones with respect to Monte Carlo convergence speed.
NASA Astrophysics Data System (ADS)
Young, Frederic; Siegel, Edward
Cook-Levin theorem theorem algorithmic computational-complexity(C-C) algorithmic-equivalence reducibility/completeness equivalence to renormalization-(semi)-group phase-transitions critical-phenomena statistical-physics universality-classes fixed-points, is exploited via Siegel FUZZYICS =CATEGORYICS = ANALOGYICS =PRAGMATYICS/CATEGORY-SEMANTICS ONTOLOGY COGNITION ANALYTICS-Aristotle ``square-of-opposition'' tabular list-format truth-table matrix analytics predicts and implements ''noise''-induced phase-transitions (NITs) to accelerate versus to decelerate Harel [Algorithmics (1987)]-Sipser[Intro.Thy. Computation(`97)] algorithmic C-C: ''NIT-picking''(!!!), to optimize optimization-problems optimally(OOPO). Versus iso-''noise'' power-spectrum quantitative-only amplitude/magnitude-only variation stochastic-resonance, ''NIT-picking'' is ''noise'' power-spectrum QUALitative-type variation via quantitative critical-exponents variation. Computer-''science''/SEANCE algorithmic C-C models: Turing-machine, finite-state-models, finite-automata,..., discrete-maths graph-theory equivalence to physics Feynman-diagrams are identified as early-days once-workable valid but limiting IMPEDING CRUTCHES(!!!), ONLY IMPEDE latter-days new-insights!!!
Spin wave Feynman diagram vertex computation package
NASA Astrophysics Data System (ADS)
Price, Alexander; Javernick, Philip; Datta, Trinanjan
Spin wave theory is a well-established theoretical technique that can correctly predict the physical behavior of ordered magnetic states. However, computing the effects of an interacting spin wave theory incorporating magnons involve a laborious by hand derivation of Feynman diagram vertices. The process is tedious and time consuming. Hence, to improve productivity and have another means to check the analytical calculations, we have devised a Feynman Diagram Vertex Computation package. In this talk, we will describe our research group's effort to implement a Mathematica based symbolic Feynman diagram vertex computation package that computes spin wave vertices. Utilizing the non-commutative algebra package NCAlgebra as an add-on to Mathematica, symbolic expressions for the Feynman diagram vertices of a Heisenberg quantum antiferromagnet are obtained. Our existing code reproduces the well-known expressions of a nearest neighbor square lattice Heisenberg model. We also discuss the case of a triangular lattice Heisenberg model where non collinear terms contribute to the vertex interactions.
Designing, programming, and optimizing a (small) quantum computer
NASA Astrophysics Data System (ADS)
Svore, Krysta
In 1982, Richard Feynman proposed to use a computer founded on the laws of quantum physics to simulate physical systems. In the more than thirty years since, quantum computers have shown promise to solve problems in number theory, chemistry, and materials science that would otherwise take longer than the lifetime of the universe to solve on an exascale classical machine. The practical realization of a quantum computer requires understanding and manipulating subtle quantum states while experimentally controlling quantum interference. It also requires an end-to-end software architecture for programming, optimizing, and implementing a quantum algorithm on the quantum device hardware. In this talk, we will introduce recent advances in connecting abstract theory to present-day real-world applications through software. We will highlight recent advancement of quantum algorithms and the challenges in ultimately performing a scalable solution on a quantum device.
An approach toward the numerical evaluation of multi-loop Feynman diagrams
NASA Astrophysics Data System (ADS)
Passarino, Giampiero
2001-12-01
A scheme for systematically achieving accurate numerical evaluation of multi-loop Feynman diagrams is developed. This shows the feasibility of a project aimed to produce a complete calculation for two-loop predictions in the Standard Model. As a first step an algorithm, proposed by F.V. Tkachov and based on the so-called generalized Bernstein functional relation, is applied to one-loop multi-leg diagrams with particular emphasis to the presence of infrared singularities, to the problem of tensorial reduction and to the classification of all singularities of a given diagram. Successively, the extension of the algorithm to two-loop diagrams is examined. The proposed solution consists in applying the functional relation to the one-loop sub-diagram which has the largest number of internal lines. In this way the integrand can be made smooth, a part from a factor which is a polynomial in xS, the vector of Feynman parameters needed for the complementary sub-diagram with the smallest number of internal lines. Since the procedure does not introduce new singularities one can distort the xS-integration hyper-contour into the complex hyper-plane, thus achieving numerical stability. The algorithm is then modified to deal with numerical evaluation around normal thresholds. Concise and practical formulas are assembled and presented, numerical results and comparisons with the available literature are shown and discussed for the so-called sunset topology.
Fuchsia : A tool for reducing differential equations for Feynman master integrals to epsilon form
NASA Astrophysics Data System (ADS)
Gituliar, Oleksandr; Magerya, Vitaly
2017-10-01
We present Fuchsia - an implementation of the Lee algorithm, which for a given system of ordinary differential equations with rational coefficients ∂x J(x , ɛ) = A(x , ɛ) J(x , ɛ) finds a basis transformation T(x , ɛ) , i.e., J(x , ɛ) = T(x , ɛ) J‧(x , ɛ) , such that the system turns into the epsilon form : ∂xJ‧(x , ɛ) = ɛ S(x) J‧(x , ɛ) , where S(x) is a Fuchsian matrix. A system of this form can be trivially solved in terms of polylogarithms as a Laurent series in the dimensional regulator ɛ. That makes the construction of the transformation T(x , ɛ) crucial for obtaining solutions of the initial system. In principle, Fuchsia can deal with any regular systems, however its primary task is to reduce differential equations for Feynman master integrals. It ensures that solutions contain only regular singularities due to the properties of Feynman integrals. Program Files doi:http://dx.doi.org/10.17632/zj6zn9vfkh.1 Licensing provisions: MIT Programming language:Python 2.7 Nature of problem: Feynman master integrals may be calculated from solutions of a linear system of differential equations with rational coefficients. Such a system can be easily solved as an ɛ-series when its epsilon form is known. Hence, a tool which is able to find the epsilon form transformations can be used to evaluate Feynman master integrals. Solution method: The solution method is based on the Lee algorithm (Lee, 2015) which consists of three main steps: fuchsification, normalization, and factorization. During the fuchsification step a given system of differential equations is transformed into the Fuchsian form with the help of the Moser method (Moser, 1959). Next, during the normalization step the system is transformed to the form where eigenvalues of all residues are proportional to the dimensional regulator ɛ. Finally, the system is factorized to the epsilon form by finding an unknown transformation which satisfies a system of linear equations. Additional comments including Restrictions and Unusual features: Systems of single-variable differential equations are considered. A system needs to be reducible to Fuchsian form and eigenvalues of its residues must be of the form n + m ɛ, where n is integer. Performance depends upon the input matrix, its size, number of singular points and their degrees. It takes around an hour to reduce an example 74 × 74 matrix with 20 singular points on a PC with a 1.7 GHz Intel Core i5 CPU. An additional slowdown is to be expected for matrices with complex and/or irrational singular point locations, as these are particularly difficult for symbolic algebra software to handle.
lsjk—a C++ library for arbitrary-precision numeric evaluation of the generalized log-sine functions
NASA Astrophysics Data System (ADS)
Kalmykov, M. Yu.; Sheplyakov, A.
2005-10-01
Generalized log-sine functions Lsj(k)(θ) appear in higher order ɛ-expansion of different Feynman diagrams. We present an algorithm for the numerical evaluation of these functions for real arguments. This algorithm is implemented as a C++ library with arbitrary-precision arithmetics for integer 0⩽k⩽9 and j⩾2. Some new relations and representations of the generalized log-sine functions are given. Program summaryTitle of program:lsjk Catalogue number:ADVS Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADVS Program obtained from: CPC Program Library, Queen's University of Belfast, N. Ireland Licensing terms: GNU General Public License Computers:all Operating systems:POSIX Programming language:C++ Memory required to execute:Depending on the complexity of the problem, at least 32 MB RAM recommended No. of lines in distributed program, including testing data, etc.:41 975 No. of bytes in distributed program, including testing data, etc.:309 156 Distribution format:tar.gz Other programs called:The CLN library for arbitrary-precision arithmetics is required at version 1.1.5 or greater External files needed:none Nature of the physical problem:Numerical evaluation of the generalized log-sine functions for real argument in the region 0<θ<π. These functions appear in Feynman integrals Method of solution:Series representation for the real argument in the region 0<θ<π Restriction on the complexity of the problem:Limited up to Lsj(9)(θ), and j is an arbitrary integer number. Thus, all function up to the weight 12 in the region 0<θ<π can be evaluated. The algorithm can be extended up to higher values of k(k>9) without modification Typical running time:Depending on the complexity of problem. See text below.
Clocks in Feynman's computer and Kitaev's local Hamiltonian: Bias, gaps, idling, and pulse tuning
NASA Astrophysics Data System (ADS)
Caha, Libor; Landau, Zeph; Nagaj, Daniel
2018-06-01
We present a collection of results about the clock in Feynman's computer construction and Kitaev's local Hamiltonian problem. First, by analyzing the spectra of quantum walks on a line with varying end-point terms, we find a better lower bound on the gap of the Feynman Hamiltonian, which translates into a less strict promise gap requirement for the quantum-Merlin-Arthur-complete local Hamiltonian problem. We also translate this result into the language of adiabatic quantum computation. Second, introducing an idling clock construction with a large state space but fast Cesaro mixing, we provide a way for achieving an arbitrarily high success probability of computation with Feynman's computer with only a logarithmic increase in the number of clock qubits. Finally, we tune and thus improve the costs (locality and gap scaling) of implementing a (pulse) clock with a single excitation.
Landau singularities from the amplituhedron
Dennen, T.; Prlina, I.; Spradlin, M.; ...
2017-06-28
We propose a simple geometric algorithm for determining the complete set of branch points of amplitudes in planar N = 4 super-Yang-Mills theory directly from the amplituhedron, without resorting to any particular representation in terms of local Feynman integrals. This represents a step towards translating integrands directly into integrals. In particular, the algorithm provides information about the symbol alphabets of general amplitudes. We illustrate the algorithm applied to the one- and two-loop MHV amplitudes.
Reduze - Feynman integral reduction in C++
NASA Astrophysics Data System (ADS)
Studerus, C.
2010-07-01
Reduze is a computer program for reducing Feynman integrals to master integrals employing a Laporta algorithm. The program is written in C++ and uses classes provided by the GiNaC library to perform the simplifications of the algebraic prefactors in the system of equations. Reduze offers the possibility to run reductions in parallel. Program summaryProgram title:Reduze Catalogue identifier: AEGE_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEGE_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions:: yes No. of lines in distributed program, including test data, etc.: 55 433 No. of bytes in distributed program, including test data, etc.: 554 866 Distribution format: tar.gz Programming language: C++ Computer: All Operating system: Unix/Linux Number of processors used: The number of processors is problem dependent. More than one possible but not arbitrary many. RAM: Depends on the complexity of the system. Classification: 4.4, 5 External routines: CLN ( http://www.ginac.de/CLN/), GiNaC ( http://www.ginac.de/) Nature of problem: Solving large systems of linear equations with Feynman integrals as unknowns and rational polynomials as prefactors. Solution method: Using a Gauss/Laporta algorithm to solve the system of equations. Restrictions: Limitations depend on the complexity of the system (number of equations, number of kinematic invariants). Running time: Depends on the complexity of the system.
Quantum Algorithms to Simulate Many-Body Physics of Correlated Fermions
NASA Astrophysics Data System (ADS)
Jiang, Zhang; Sung, Kevin J.; Kechedzhi, Kostyantyn; Smelyanskiy, Vadim N.; Boixo, Sergio
2018-04-01
Simulating strongly correlated fermionic systems is notoriously hard on classical computers. An alternative approach, as proposed by Feynman, is to use a quantum computer. We discuss simulating strongly correlated fermionic systems using near-term quantum devices. We focus specifically on two-dimensional (2D) or linear geometry with nearest-neighbor qubit-qubit couplings, typical for superconducting transmon qubit arrays. We improve an existing algorithm to prepare an arbitrary Slater determinant by exploiting a unitary symmetry. We also present a quantum algorithm to prepare an arbitrary fermionic Gaussian state with O (N2) gates and O (N ) circuit depth. Both algorithms are optimal in the sense that the numbers of parameters in the quantum circuits are equal to those describing the quantum states. Furthermore, we propose an algorithm to implement the 2D fermionic Fourier transformation on a 2D qubit array with only O (N1.5) gates and O (√{N }) circuit depth, which is the minimum depth required for quantum information to travel across the qubit array. We also present methods to simulate each time step in the evolution of the 2D Fermi-Hubbard model—again on a 2D qubit array—with O (N ) gates and O (√{N }) circuit depth. Finally, we discuss how these algorithms can be used to determine the ground-state properties and phase diagrams of strongly correlated quantum systems using the Hubbard model as an example.
Smith, Kyle K.G.; Poulsen, Jens Aage; Nyman, Gunnar; ...
2015-06-30
Here, we apply the Feynman-Kleinert Quasi-Classical Wigner (FK-QCW) method developed in our previous work [Smith et al., J. Chem. Phys. 142, 244112 (2015)] for the determination of the dynamic structure factor of liquid para-hydrogen and ortho-deuterium at state points of (T = 20.0 K, n = 21.24 nm -3) and (T = 23.0 K, n = 24.61 nm -3), respectively. When applied to this challenging system, it is shown that this new FK-QCW method consistently reproduces the experimental dynamic structure factor reported by Smith et al. [J. Chem. Phys. 140, 034501 (2014)] for all momentum transfers considered. Moreover, this showsmore » that FK-QCW provides a substantial improvement over the Feynman-Kleinert linearized path-integral method, in which purely classical dynamics are used. Furthermore, for small momentum transfers, it is shown that FK-QCW provides nearly the same results as ring-polymer molecular dynamics (RPMD), thus suggesting that FK-QCW provides a potentially more appealing algorithm than RPMD since it is not formally limited to correlation functions involving linear operators.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Smith, Kyle K.G.; Poulsen, Jens Aage; Nyman, Gunnar
Here, we apply the Feynman-Kleinert Quasi-Classical Wigner (FK-QCW) method developed in our previous work [Smith et al., J. Chem. Phys. 142, 244112 (2015)] for the determination of the dynamic structure factor of liquid para-hydrogen and ortho-deuterium at state points of (T = 20.0 K, n = 21.24 nm -3) and (T = 23.0 K, n = 24.61 nm -3), respectively. When applied to this challenging system, it is shown that this new FK-QCW method consistently reproduces the experimental dynamic structure factor reported by Smith et al. [J. Chem. Phys. 140, 034501 (2014)] for all momentum transfers considered. Moreover, this showsmore » that FK-QCW provides a substantial improvement over the Feynman-Kleinert linearized path-integral method, in which purely classical dynamics are used. Furthermore, for small momentum transfers, it is shown that FK-QCW provides nearly the same results as ring-polymer molecular dynamics (RPMD), thus suggesting that FK-QCW provides a potentially more appealing algorithm than RPMD since it is not formally limited to correlation functions involving linear operators.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Smith, Kyle K. G., E-mail: kylesmith@utexas.edu; Poulsen, Jens Aage, E-mail: jens72@chem.gu.se; Nyman, Gunnar, E-mail: nyman@chem.gu.se
We apply the Feynman-Kleinert Quasi-Classical Wigner (FK-QCW) method developed in our previous work [Smith et al., J. Chem. Phys. 142, 244112 (2015)] for the determination of the dynamic structure factor of liquid para-hydrogen and ortho-deuterium at state points of (T = 20.0 K, n = 21.24 nm{sup −3}) and (T = 23.0 K, n = 24.61 nm{sup −3}), respectively. When applied to this challenging system, it is shown that this new FK-QCW method consistently reproduces the experimental dynamic structure factor reported by Smith et al. [J. Chem. Phys. 140, 034501 (2014)] for all momentum transfers considered. This shows that FK-QCWmore » provides a substantial improvement over the Feynman-Kleinert linearized path-integral method, in which purely classical dynamics are used. Furthermore, for small momentum transfers, it is shown that FK-QCW provides nearly the same results as ring-polymer molecular dynamics (RPMD), thus suggesting that FK-QCW provides a potentially more appealing algorithm than RPMD since it is not formally limited to correlation functions involving linear operators.« less
Smith, Kyle K G; Poulsen, Jens Aage; Nyman, Gunnar; Cunsolo, Alessandro; Rossky, Peter J
2015-06-28
We apply the Feynman-Kleinert Quasi-Classical Wigner (FK-QCW) method developed in our previous work [Smith et al., J. Chem. Phys. 142, 244112 (2015)] for the determination of the dynamic structure factor of liquid para-hydrogen and ortho-deuterium at state points of (T = 20.0 K, n = 21.24 nm(-3)) and (T = 23.0 K, n = 24.61 nm(-3)), respectively. When applied to this challenging system, it is shown that this new FK-QCW method consistently reproduces the experimental dynamic structure factor reported by Smith et al. [J. Chem. Phys. 140, 034501 (2014)] for all momentum transfers considered. This shows that FK-QCW provides a substantial improvement over the Feynman-Kleinert linearized path-integral method, in which purely classical dynamics are used. Furthermore, for small momentum transfers, it is shown that FK-QCW provides nearly the same results as ring-polymer molecular dynamics (RPMD), thus suggesting that FK-QCW provides a potentially more appealing algorithm than RPMD since it is not formally limited to correlation functions involving linear operators.
NASA Astrophysics Data System (ADS)
Sasamal, Trailokya Nath; Singh, Ashutosh Kumar; Ghanekar, Umesh
2018-04-01
Nanotechnologies, remarkably Quantum-dot Cellular Automata (QCA), offer an attractive perspective for future computing technologies. In this paper, QCA is investigated as an implementation method for designing area and power efficient reversible logic gates. The proposed designs achieve superior performance by incorporating a compact 2-input XOR gate. The proposed design for Feynman, Toffoli, and Fredkin gates demonstrates 28.12, 24.4, and 7% reduction in cell count and utilizes 46, 24.4, and 7.6% less area, respectively over previous best designs. Regarding the cell count (area cover) that of the proposed Peres gate and Double Feynman gate are 44.32% (21.5%) and 12% (25%), respectively less than the most compact previous designs. Further, the delay of Fredkin and Toffoli gates is 0.75 clock cycles, which is equal to the delay of the previous best designs. While the Feynman and Double Feynman gates achieve a delay of 0.5 clock cycles, equal to the least delay previous one. Energy analysis confirms that the average energy dissipation of the developed Feynman, Toffoli, and Fredkin gates is 30.80, 18.08, and 4.3% (for 1.0 E k energy level), respectively less compared to best reported designs. This emphasizes the beneficial role of using proposed reversible gates to design complex and power efficient QCA circuits. The QCADesigner tool is used to validate the layout of the proposed designs, and the QCAPro tool is used to evaluate the energy dissipation.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Butko, Yana A., E-mail: yanabutko@yandex.ru, E-mail: kinderknecht@math.uni-sb.de; Grothaus, Martin, E-mail: grothaus@mathematik.uni-kl.de; Smolyanov, Oleg G., E-mail: Smolyanov@yandex.ru
2016-02-15
Evolution semigroups generated by pseudo-differential operators are considered. These operators are obtained by different (parameterized by a number τ) procedures of quantization from a certain class of functions (or symbols) defined on the phase space. This class contains Hamilton functions of particles with variable mass in magnetic and potential fields and more general symbols given by the Lévy-Khintchine formula. The considered semigroups are represented as limits of n-fold iterated integrals when n tends to infinity. Such representations are called Feynman formulae. Some of these representations are constructed with the help of another pseudo-differential operator, obtained by the same procedure ofmore » quantization; such representations are called Hamiltonian Feynman formulae. Some representations are based on integral operators with elementary kernels; these are called Lagrangian Feynman formulae. Langrangian Feynman formulae provide approximations of evolution semigroups, suitable for direct computations and numerical modeling of the corresponding dynamics. Hamiltonian Feynman formulae allow to represent the considered semigroups by means of Feynman path integrals. In the article, a family of phase space Feynman pseudomeasures corresponding to different procedures of quantization is introduced. The considered evolution semigroups are represented as phase space Feynman path integrals with respect to these Feynman pseudomeasures, i.e., different quantizations correspond to Feynman path integrals with the same integrand but with respect to different pseudomeasures. This answers Berezin’s problem of distinguishing a procedure of quantization on the language of Feynman path integrals. Moreover, the obtained Lagrangian Feynman formulae allow also to calculate these phase space Feynman path integrals and to connect them with some functional integrals with respect to probability measures.« less
Time-ordered product expansions for computational stochastic system biology.
Mjolsness, Eric
2013-06-01
The time-ordered product framework of quantum field theory can also be used to understand salient phenomena in stochastic biochemical networks. It is used here to derive Gillespie's stochastic simulation algorithm (SSA) for chemical reaction networks; consequently, the SSA can be interpreted in terms of Feynman diagrams. It is also used here to derive other, more general simulation and parameter-learning algorithms including simulation algorithms for networks of stochastic reaction-like processes operating on parameterized objects, and also hybrid stochastic reaction/differential equation models in which systems of ordinary differential equations evolve the parameters of objects that can also undergo stochastic reactions. Thus, the time-ordered product expansion can be used systematically to derive simulation and parameter-fitting algorithms for stochastic systems.
Development of tight-binding based GW algorithm and its computational implementation for graphene
DOE Office of Scientific and Technical Information (OSTI.GOV)
Majidi, Muhammad Aziz; NUSNNI-NanoCore, Department of Physics, National University of Singapore; Singapore Synchrotron Light Source
Graphene has been a hot subject of research in the last decade as it holds a promise for various applications. One interesting issue is whether or not graphene should be classified into a strongly or weakly correlated system, as the optical properties may change upon several factors, such as the substrate, voltage bias, adatoms, etc. As the Coulomb repulsive interactions among electrons can generate the correlation effects that may modify the single-particle spectra (density of states) and the two-particle spectra (optical conductivity) of graphene, we aim to explore such interactions in this study. The understanding of such correlation effects ismore » important because eventually they play an important role in inducing the effective attractive interactions between electrons and holes that bind them into excitons. We do this study theoretically by developing a GW method implemented on the basis of the tight-binding (TB) model Hamiltonian. Unlike the well-known GW method developed within density functional theory (DFT) framework, our TB-based GW implementation may serve as an alternative technique suitable for systems which Hamiltonian is to be constructed through a tight-binding based or similar models. This study includes theoretical formulation of the Green’s function G, the renormalized interaction function W from random phase approximation (RPA), and the corresponding self energy derived from Feynman diagrams, as well as the development of the algorithm to compute those quantities. As an evaluation of the method, we perform calculations of the density of states and the optical conductivity of graphene, and analyze the results.« less
From Feynman rules to conserved quantum numbers, I
NASA Astrophysics Data System (ADS)
Nogueira, P.
2017-05-01
In the context of Quantum Field Theory (QFT) there is often the need to find sets of graph-like diagrams (the so-called Feynman diagrams) for a given physical model. If negative, the answer to the related problem 'Are there any diagrams with this set of external fields?' may settle certain physical questions at once. Here the latter problem is formulated in terms of a system of linear diophantine equations derived from the Lagrangian density, from which necessary conditions for the existence of the required diagrams may be obtained. Those conditions are equalities that look like either linear diophantine equations or linear modular (i.e. congruence) equations, and may be found by means of fairly simple algorithms that involve integer computations. The diophantine equations so obtained represent (particle) number conservation rules, and are related to the conserved (additive) quantum numbers that may be assigned to the fields of the model.
Iterative blip-summed path integral for quantum dynamics in strongly dissipative environments
NASA Astrophysics Data System (ADS)
Makri, Nancy
2017-04-01
The iterative decomposition of the blip-summed path integral [N. Makri, J. Chem. Phys. 141, 134117 (2014)] is described. The starting point is the expression of the reduced density matrix for a quantum system interacting with a harmonic dissipative bath in the form of a forward-backward path sum, where the effects of the bath enter through the Feynman-Vernon influence functional. The path sum is evaluated iteratively in time by propagating an array that stores blip configurations within the memory interval. Convergence with respect to the number of blips and the memory length yields numerically exact results which are free of statistical error. In situations of strongly dissipative, sluggish baths, the algorithm leads to a dramatic reduction of computational effort in comparison with iterative path integral methods that do not implement the blip decomposition. This gain in efficiency arises from (i) the rapid convergence of the blip series and (ii) circumventing the explicit enumeration of between-blip path segments, whose number grows exponentially with the memory length. Application to an asymmetric dissipative two-level system illustrates the rapid convergence of the algorithm even when the bath memory is extremely long.
Polynomial complexity despite the fermionic sign
NASA Astrophysics Data System (ADS)
Rossi, R.; Prokof'ev, N.; Svistunov, B.; Van Houcke, K.; Werner, F.
2017-04-01
It is commonly believed that in unbiased quantum Monte Carlo approaches to fermionic many-body problems, the infamous sign problem generically implies prohibitively large computational times for obtaining thermodynamic-limit quantities. We point out that for convergent Feynman diagrammatic series evaluated with a recently introduced Monte Carlo algorithm (see Rossi R., arXiv:1612.05184), the computational time increases only polynomially with the inverse error on thermodynamic-limit quantities.
A Note on the Stochastic Nature of Feynman Quantum Paths
NASA Astrophysics Data System (ADS)
Botelho, Luiz C. L.
2016-11-01
We propose a Fresnel stochastic white noise framework to analyze the stochastic nature of the Feynman paths entering on the Feynman Path Integral expression for the Feynman Propagator of a particle quantum mechanically moving under a time-independent potential.
A Note on Feynman Path Integral for Electromagnetic External Fields
NASA Astrophysics Data System (ADS)
Botelho, Luiz C. L.
2017-08-01
We propose a Fresnel stochastic white noise framework to analyze the nature of the Feynman paths entering on the Feynman Path Integral expression for the Feynman Propagator of a particle quantum mechanically moving under an external electromagnetic time-independent potential.
CalcHEP 3.4 for collider physics within and beyond the Standard Model
NASA Astrophysics Data System (ADS)
Belyaev, Alexander; Christensen, Neil D.; Pukhov, Alexander
2013-07-01
We present version 3.4 of the CalcHEP software package which is designed for effective evaluation and simulation of high energy physics collider processes at parton level. The main features of CalcHEP are the computation of Feynman diagrams, integration over multi-particle phase space and event simulation at parton level. The principle attractive key-points along these lines are that it has: (a) an easy startup and usage even for those who are not familiar with CalcHEP and programming; (b) a friendly and convenient graphical user interface (GUI); (c) the option for the user to easily modify a model or introduce a new model by either using the graphical interface or by using an external package with the possibility of cross checking the results in different gauges; (d) a batch interface which allows to perform very complicated and tedious calculations connecting production and decay modes for processes with many particles in the final state. With this features set, CalcHEP can efficiently perform calculations with a high level of automation from a theory in the form of a Lagrangian down to phenomenology in the form of cross sections, parton level event simulation and various kinematical distributions. In this paper we report on the new features of CalcHEP 3.4 which improves the power of our package to be an effective tool for the study of modern collider phenomenology. Program summaryProgram title: CalcHEP Catalogue identifier: AEOV_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEOV_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 78535 No. of bytes in distributed program, including test data, etc.: 818061 Distribution format: tar.gz Programming language: C. Computer: PC, MAC, Unix Workstations. Operating system: Unix. RAM: Depends on process under study Classification: 4.4, 5. External routines: X11 Nature of problem: Implement new models of particle interactions. Generate Feynman diagrams for a physical process in any implemented theoretical model. Integrate phase space for Feynman diagrams to obtain cross sections or particle widths taking into account kinematical cuts. Simulate collisions at modern colliders and generate respective unweighted events. Mix events for different subprocesses and connect them with the decays of unstable particles. Solution method: Symbolic calculations. Squared Feynman diagram approach Vegas Monte Carlo algorithm. Restrictions: Up to 2→4 production (1→5 decay) processes are realistic on typical computers. Higher multiplicities sometimes possible for specific 2→5 and 2→6 processes. Unusual features: Graphical user interface, symbolic algebra calculation of squared matrix element, parallelization on a pbs cluster. Running time: Depends strongly on the process. For a typical 2→2 process it takes seconds. For 2→3 processes the typical running time is of the order of minutes. For higher multiplicities it could take much longer.
A Celebration of Richard Feynman
DOE Office of Scientific and Technical Information (OSTI.GOV)
Feynman, Richard
In honor of the 2005 World Year of Physics, on the birthday of Nobel Prize-winning physicist Richard Feynman, BSA sponsored this celebration. Actor Norman Parker reads from Feynman's bestselling books, and Ralph Leighton and Tom Rutishauser, who played bongos with Feynman, reminisce on what it was like to drum with him.
A Celebration of Richard Feynman
Feynman, Richard
2018-01-05
In honor of the 2005 World Year of Physics, on the birthday of Nobel Prize-winning physicist Richard Feynman, BSA sponsored this celebration. Actor Norman Parker reads from Feynman's bestselling books, and Ralph Leighton and Tom Rutishauser, who played bongos with Feynman, reminisce on what it was like to drum with him.
Richard Feynman and computation
NASA Astrophysics Data System (ADS)
Hey, Tony
1999-04-01
The enormous contribution of Richard Feynman to modern physics is well known, both to teaching through his famous Feynman Lectures on Physics, and to research with his Feynman diagram approach to quantum field theory and his path integral formulation of quantum mechanics. Less well known perhaps is his long-standing interest in the physics of computation and this is the subject of this paper. Feynman lectured on computation at Caltech for most of the last decade of his life, first with John Hopfield and Carver Mead, and then with Gerry Sussman. The story of how these lectures came to be written up as the Feynman Lectures on Computation is briefly recounted. Feynman also discussed the fundamentals of computation with other legendary figures of the computer science and physics community such as Ed Fredkin, Rolf Landauer, Carver Mead, Marvin Minsky and John Wheeler. He was also instrumental in stimulating developments in both nanotechnology and quantum computing. During the 1980s Feynman re-visited long-standing interests both in parallel computing with Geoffrey Fox and Danny Hillis, and in reversible computation and quantum computing with Charles Bennett, Norman Margolus, Tom Toffoli and Wojciech Zurek. This paper records Feynman's links with the computational community and includes some reminiscences about his involvement with the fundamentals of computing.
Stochastic, real-space, imaginary-time evaluation of third-order Feynman-Goldstone diagrams
NASA Astrophysics Data System (ADS)
Willow, Soohaeng Yoo; Hirata, So
2014-01-01
A new, alternative set of interpretation rules of Feynman-Goldstone diagrams for many-body perturbation theory is proposed, which translates diagrams into algebraic expressions suitable for direct Monte Carlo integrations. A vertex of a diagram is associated with a Coulomb interaction (rather than a two-electron integral) and an edge with the trace of a Green's function in real space and imaginary time. With these, 12 diagrams of third-order many-body perturbation (MP3) theory are converted into 20-dimensional integrals, which are then evaluated by a Monte Carlo method. It uses redundant walkers for convergence acceleration and a weight function for importance sampling in conjunction with the Metropolis algorithm. The resulting Monte Carlo MP3 method has low-rank polynomial size dependence of the operation cost, a negligible memory cost, and a naturally parallel computational kernel, while reproducing the correct correlation energies of small molecules within a few mEh after 106 Monte Carlo steps.
Feynman diagrams and rooted maps
NASA Astrophysics Data System (ADS)
Prunotto, Andrea; Alberico, Wanda Maria; Czerski, Piotr
2018-04-01
The rooted maps theory, a branch of the theory of homology, is shown to be a powerful tool for investigating the topological properties of Feynman diagrams, related to the single particle propagator in the quantum many-body systems. The numerical correspondence between the number of this class of Feynman diagrams as a function of perturbative order and the number of rooted maps as a function of the number of edges is studied. A graphical procedure to associate Feynman diagrams and rooted maps is then stated. Finally, starting from rooted maps principles, an original definition of the genus of a Feynman diagram, which totally differs from the usual one, is given.
NASA Astrophysics Data System (ADS)
Prayogi, A.; Majidi, M. A.
2017-07-01
In condensed-matter physics, strongly-correlated systems refer to materials that exhibit variety of fascinating properties and ordered phases, depending on temperature, doping, and other factors. Such unique properties most notably arise due to strong electron-electron interactions, and in some cases due to interactions involving other quasiparticles as well. Electronic correlation effects are non-trivial that one may need a sufficiently accurate approximation technique with quite heavy computation, such as Quantum Monte-Carlo, in order to capture particular material properties arising from such effects. Meanwhile, less accurate techniques may come with lower numerical cost, but the ability to capture particular properties may highly depend on the choice of approximation. Among the many-body techniques derivable from Feynman diagrams, we aim to formulate algorithmic implementation of the Ladder Diagram approximation to capture the effects of electron-electron interactions. We wish to investigate how these correlation effects influence the temperature-dependent properties of strongly-correlated metals and semiconductors. As we are interested to study the temperature-dependent properties of the system, the Ladder diagram method needs to be applied in Matsubara frequency domain to obtain the self-consistent self-energy. However, at the end we would also need to compute the dynamical properties like density of states (DOS) and optical conductivity that are defined in the real frequency domain. For this purpose, we need to perform the analytic continuation procedure. At the end of this study, we will test the technique by observing the occurrence of metal-insulator transition in strongly-correlated metals, and renormalization of the band gap in strongly-correlated semiconductors.
Efficient numerical evaluation of Feynman integrals
NASA Astrophysics Data System (ADS)
Li, Zhao; Wang, Jian; Yan, Qi-Shu; Zhao, Xiaoran
2016-03-01
Feynman loop integrals are a key ingredient for the calculation of higher order radiation effects, and are responsible for reliable and accurate theoretical prediction. We improve the efficiency of numerical integration in sector decomposition by implementing a quasi-Monte Carlo method associated with the CUDA/GPU technique. For demonstration we present the results of several Feynman integrals up to two loops in both Euclidean and physical kinematic regions in comparison with those obtained from FIESTA3. It is shown that both planar and non-planar two-loop master integrals in the physical kinematic region can be evaluated in less than half a minute with accuracy, which makes the direct numerical approach viable for precise investigation of higher order effects in multi-loop processes, e.g. the next-to-leading order QCD effect in Higgs pair production via gluon fusion with a finite top quark mass. Supported by the Natural Science Foundation of China (11305179 11475180), Youth Innovation Promotion Association, CAS, IHEP Innovation (Y4545170Y2), State Key Lab for Electronics and Particle Detectors, Open Project Program of State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, China (Y4KF061CJ1), Cluster of Excellence Precision Physics, Fundamental Interactions and Structure of Matter (PRISMA-EXC 1098)
A Maple package for computing Gröbner bases for linear recurrence relations
NASA Astrophysics Data System (ADS)
Gerdt, Vladimir P.; Robertz, Daniel
2006-04-01
A Maple package for computing Gröbner bases of linear difference ideals is described. The underlying algorithm is based on Janet and Janet-like monomial divisions associated with finite difference operators. The package can be used, for example, for automatic generation of difference schemes for linear partial differential equations and for reduction of multiloop Feynman integrals. These two possible applications are illustrated by simple examples of the Laplace equation and a one-loop scalar integral of propagator type.
Automated generation of lattice QCD Feynman rules
NASA Astrophysics Data System (ADS)
Hart, A.; von Hippel, G. M.; Horgan, R. R.; Müller, E. H.
2009-12-01
The derivation of the Feynman rules for lattice perturbation theory from actions and operators is complicated, especially for highly improved actions such as HISQ. This task is, however, both important and particularly suitable for automation. We describe a suite of software to generate and evaluate Feynman rules for a wide range of lattice field theories with gluons and (relativistic and/or heavy) quarks. Our programs are capable of dealing with actions as complicated as (m)NRQCD and HISQ. Automated differentiation methods are used to calculate also the derivatives of Feynman diagrams. Program summaryProgram title: HiPPY, HPsrc Catalogue identifier: AEDX_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEDX_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GPLv2 (see Additional comments below) No. of lines in distributed program, including test data, etc.: 513 426 No. of bytes in distributed program, including test data, etc.: 4 893 707 Distribution format: tar.gz Programming language: Python, Fortran95 Computer: HiPPy: Single-processor workstations. HPsrc: Single-processor workstations and MPI-enabled multi-processor systems Operating system: HiPPy: Any for which Python v2.5.x is available. HPsrc: Any for which a standards-compliant Fortran95 compiler is available Has the code been vectorised or parallelised?: Yes RAM: Problem specific, typically less than 1 GB for either code Classification: 4.4, 11.5 Nature of problem: Derivation and use of perturbative Feynman rules for complicated lattice QCD actions. Solution method: An automated expansion method implemented in Python (HiPPy) and code to use expansions to generate Feynman rules in Fortran95 (HPsrc). Restrictions: No general restrictions. Specific restrictions are discussed in the text. Additional comments: The HiPPy and HPsrc codes are released under the second version of the GNU General Public Licence (GPL v2). Therefore anyone is free to use or modify the code for their own calculations. As part of the licensing, we ask that any publications including results from the use of this code or of modifications of it cite Refs. [1,2] as well as this paper. Finally, we also ask that details of these publications, as well as of any bugs or required or useful improvements of this core code, would be communicated to us. Running time: Very problem specific, depending on the complexity of the Feynman rules and the number of integration points. Typically between a few minutes and several weeks. The installation tests provided with the program code take only a few seconds to run. References:A. Hart, G.M. von Hippel, R.R. Horgan, L.C. Storoni, Automatically generating Feynman rules for improved lattice eld theories, J. Comput. Phys. 209 (2005) 340-353, doi:10.1016/j.jcp.2005.03.010, arXiv:hep-lat/0411026. M. Lüscher, P. Weisz, Efficient Numerical Techniques for Perturbative Lattice Gauge Theory Computations, Nucl. Phys. B 266 (1986) 309, doi:10.1016/0550-3213(86)90094-5.
Towards a feasible implementation of quantum neural networks using quantum dots
DOE Office of Scientific and Technical Information (OSTI.GOV)
Altaisky, Mikhail V., E-mail: altaisky@mx.iki.rssi.ru, E-mail: nzolnik@iki.rssi.ru; Zolnikova, Nadezhda N., E-mail: altaisky@mx.iki.rssi.ru, E-mail: nzolnik@iki.rssi.ru; Kaputkina, Natalia E., E-mail: nataly@misis.ru
2016-03-07
We propose an implementation of quantum neural networks using an array of quantum dots with dipole-dipole interactions. We demonstrate that this implementation is both feasible and versatile by studying it within the framework of GaAs based quantum dot qubits coupled to a reservoir of acoustic phonons. Using numerically exact Feynman integral calculations, we have found that the quantum coherence in our neural networks survive for over a hundred ps even at liquid nitrogen temperatures (77 K), which is three orders of magnitude higher than current implementations, which are based on SQUID-based systems operating at temperatures in the mK range.
ALOHA: Automatic libraries of helicity amplitudes for Feynman diagram computations
NASA Astrophysics Data System (ADS)
de Aquino, Priscila; Link, William; Maltoni, Fabio; Mattelaer, Olivier; Stelzer, Tim
2012-10-01
We present an application that automatically writes the HELAS (HELicity Amplitude Subroutines) library corresponding to the Feynman rules of any quantum field theory Lagrangian. The code is written in Python and takes the Universal FeynRules Output (UFO) as an input. From this input it produces the complete set of routines, wave-functions and amplitudes, that are needed for the computation of Feynman diagrams at leading as well as at higher orders. The representation is language independent and currently it can output routines in Fortran, C++, and Python. A few sample applications implemented in the MADGRAPH 5 framework are presented. Program summary Program title: ALOHA Catalogue identifier: AEMS_v1_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEMS_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: http://www.opensource.org/licenses/UoI-NCSA.php No. of lines in distributed program, including test data, etc.: 6094320 No. of bytes in distributed program, including test data, etc.: 7479819 Distribution format: tar.gz Programming language: Python2.6 Computer: 32/64 bit Operating system: Linux/Mac/Windows RAM: 512 Mbytes Classification: 4.4, 11.6 Nature of problem: An effcient numerical evaluation of a squared matrix element can be done with the help of the helicity routines implemented in the HELAS library [1]. This static library contains a limited number of helicity functions and is therefore not always able to provide the needed routine in the presence of an arbitrary interaction. This program provides a way to automatically create the corresponding routines for any given model. Solution method: ALOHA takes the Feynman rules associated to the vertex obtained from the model information (in the UFO format [2]), and multiplies it by the different wavefunctions or propagators. As a result the analytical expression of the helicity routines is obtained. Subsequently, this expression is automatically written in the requested language (Python, Fortran or C++) Restrictions: The allowed fields are currently spin 0, 1/2, 1 and 2, and the propagators of these particles are canonical. Running time: A few seconds for the SM and the MSSM, and up to a few minutes for models with spin 2 particles. References: [1] Murayama, H. and Watanabe, I. and Hagiwara, K., HELAS: HELicity Amplitude Subroutines for Feynman diagram evaluations, KEK-91-11, (1992) http://www-lib.kek.jp/cgi-bin/img_index?199124011 [2] C. Degrande, C. Duhr, B. Fuks, D. Grellscheid, O. Mattelaer, et al., UFO— The Universal FeynRules Output, Comput. Phys. Commun. 183 (2012) 1201-1214. arXiv:1108.2040, doi:10.1016/j.cpc.2012.01.022.
The electromigration force in metallic bulk
NASA Astrophysics Data System (ADS)
Lodder, A.; Dekker, J. P.
1998-01-01
The voltage induced driving force on a migrating atom in a metallic system is discussed in the perspective of the Hellmann-Feynman force concept, local screening concepts and the linear-response approach. Since the force operator is well defined in quantum mechanics it appears to be only confusing to refer to the Hellmann-Feynman theorem in the context of electromigration. Local screening concepts are shown to be mainly of historical value. The physics involved is completely represented in ab initio local density treatments of dilute alloys and the implementation does not require additional precautions about screening, being typical for jellium treatments. The linear-response approach is shown to be a reliable guide in deciding about the two contributions to the driving force, the direct force and the wind force. Results are given for the wind valence for electromigration in a number of FCC and BCC metals, calculated using an ab initio KKR-Green's function description of a dilute alloy.
Richard P. Feynman Center for Innovation
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A Model for Bilingual Physics Teaching: "The Feynman Lectures "
NASA Astrophysics Data System (ADS)
Metzner, Heqing W.
2006-12-01
Feynman was not only a great physicist but also a remarkably effective educator. The Feynman Lectures on Physics originally published in 1963 were designed to be GUIDES for teachers and for gifted students. More than 40 years later, his peculiar teaching ideas have special application to bilingual physics teaching in China because: (1) Each individual lecture provides a self contained unit for bilingual teaching; (2)The lectures broaden the physics understanding of students; and (3)Feynman's original thought in English is experienced through the bilingual teaching of physics.
NASA Astrophysics Data System (ADS)
Motta, Mario; Zhang, Shiwei
2018-05-01
We propose an algorithm for accurate, systematic, and scalable computation of interatomic forces within the auxiliary-field quantum Monte Carlo (AFQMC) method. The algorithm relies on the Hellmann-Feynman theorem and incorporates Pulay corrections in the presence of atomic orbital basis sets. We benchmark the method for small molecules by comparing the computed forces with the derivatives of the AFQMC potential energy surface and by direct comparison with other quantum chemistry methods. We then perform geometry optimizations using the steepest descent algorithm in larger molecules. With realistic basis sets, we obtain equilibrium geometries in agreement, within statistical error bars, with experimental values. The increase in computational cost for computing forces in this approach is only a small prefactor over that of calculating the total energy. This paves the way for a general and efficient approach for geometry optimization and molecular dynamics within AFQMC.
Revisiting Feynman's ratchet with thermoelectric transport theory.
Apertet, Y; Ouerdane, H; Goupil, C; Lecoeur, Ph
2014-07-01
We show how the formalism used for thermoelectric transport may be adapted to Smoluchowski's seminal thought experiment, also known as Feynman's ratchet and pawl system. Our analysis rests on the notion of useful flux, which for a thermoelectric system is the electrical current and for Feynman's ratchet is the effective jump frequency. Our approach yields original insight into the derivation and analysis of the system's properties. In particular we define an entropy per tooth in analogy with the entropy per carrier or Seebeck coefficient, and we derive the analog to Kelvin's second relation for Feynman's ratchet. Owing to the formal similarity between the heat fluxes balance equations for a thermoelectric generator (TEG) and those for Feynman's ratchet, we introduce a distribution parameter γ that quantifies the amount of heat that flows through the cold and hot sides of both heat engines. While it is well established that γ = 1/2 for a TEG, it is equal to 1 for Feynman's ratchet. This implies that no heat may be rejected in the cold reservoir for the latter case. Further, the analysis of the efficiency at maximum power shows that the so-called Feynman efficiency corresponds to that of an exoreversible engine, with γ = 1. Then, turning to the nonlinear regime, we generalize the approach based on the convection picture and introduce two different types of resistance to distinguish the dynamical behavior of the considered system from its ability to dissipate energy. We finally put forth the strong similarity between the original Feynman ratchet and a mesoscopic thermoelectric generator with a single conducting channel.
Feynman's and Ohta's Models of a Josephson Junction
ERIC Educational Resources Information Center
De Luca, R.
2012-01-01
The Josephson equations are derived by means of the weakly coupled two-level quantum system model given by Feynman. Adopting a simplified version of Ohta's model, starting from Feynman's model, the strict voltage-frequency Josephson relation is derived. The contribution of Ohta's approach to the comprehension of the additional term given by the…
Spin foam models for quantum gravity
NASA Astrophysics Data System (ADS)
Perez, Alejandro
The definition of a quantum theory of gravity is explored following Feynman's path-integral approach. The aim is to construct a well defined version of the Wheeler-Misner- Hawking ``sum over four geometries'' formulation of quantum general relativity (GR). This is done by means of exploiting the similarities between the formulation of GR in terms of tetrad-connection variables (Palatini formulation) and a simpler theory called BF theory. One can go from BF theory to GR by imposing certain constraints on the BF-theory configurations. BF theory contains only global degrees of freedom (topological theory) and it can be exactly quantized á la Feynman introducing a discretization of the manifold. Using the path integral for BF theory we define a path integration for GR imposing the BF-to-GR constraints on the BF measure. The infinite degrees of freedom of gravity are restored in the process, and the restriction to a single discretization introduces a cut- off in the summed-over configurations. In order to capture all the degrees of freedom a sum over discretization is implemented. Both the implementation of the BF-to-GR constraints and the sum over discretizations are obtained by means of the introduction of an auxiliary field theory (AFT). 4-geometries in the path integral for GR are given by the Feynman diagrams of the AFT which is in this sense dual to GR. Feynman diagrams correspond to 2-complexes labeled by unitary irreducible representations of the internal gauge group (corresponding to tetrad rotation in the connection to GR). A model for 4-dimensional Euclidean quantum gravity (QG) is defined which corresponds to a different normalization of the Barrett-Crane model. The model is perturbatively finite; divergences appearing in the Barrett-Crane model are cured by the new normalization. We extend our techniques to the Lorentzian sector, where we define two models for four-dimensional QG. The first one contains only time-like representations and is shown to be perturbatively finite. The second model contains both time-like and space-like representations. The spectrum of geometrical operators coincide with the prediction of the canonical approach of loop QG. At the moment, the convergence properties of the model are less understood and remain for future investigation.
Feynman propagators on static spacetimes
NASA Astrophysics Data System (ADS)
Dereziński, Jan; Siemssen, Daniel
We consider the Klein-Gordon equation on a static spacetime and minimally coupled to a static electromagnetic potential. We show that it is essentially self-adjoint on Cc∞. We discuss various distinguished inverses and bisolutions of the Klein-Gordon operator, focusing on the so-called Feynman propagator. We show that the Feynman propagator can be considered the boundary value of the resolvent of the Klein-Gordon operator, in the spirit of the limiting absorption principle known from the theory of Schrödinger operators. We also show that the Feynman propagator is the limit of the inverse of the Wick rotated Klein-Gordon operator.
NASA Astrophysics Data System (ADS)
Preskill, John
2008-12-01
In the popular imagination, the iconic American theoretical physicist is Richard Feynman, in all his safe-cracking, bongo-thumping, woman-chasing glory. I suspect that many physicists, if asked to name a living colleague who best captures the spirit of Feynman, would give the same answer as me: Leonard Susskind. As far as I know, Susskind does not crack safes, thump bongos, or chase women, yet he shares Feynman's brash cockiness (which in Susskind's case is leavened by occasional redeeming flashes of self-deprecation) and Feynman's gift for spinning fascinating anecdotes. If you are having a group of physicists over for dinner and want to be sure to have a good time, invite Susskind.
NASA Technical Reports Server (NTRS)
Steiner, E.
1973-01-01
The use of the electrostatic Hellmann-Feynman theorem for the calculation of the leading term in the 1/R expansion of the force of interaction between two well-separated hydrogen atoms is discussed. Previous work has suggested that whereas this term is determined wholly by the first-order wavefunction when calculated by perturbation theory, the use of the Hellmann-Feynman theorem apparently requires the wavefunction through second order. It is shown how the two results may be reconciled and that the Hellmann-Feynman theorem may be reformulated in such a way that only the first-order wavefunction is required.
Counting the number of Feynman graphs in QCD
NASA Astrophysics Data System (ADS)
Kaneko, T.
2018-05-01
Information about the number of Feynman graphs for a given physical process in a given field theory is especially useful for confirming the result of a Feynman graph generator used in an automatic system of perturbative calculations. A method of counting the number of Feynman graphs with weight of symmetry factor was established based on zero-dimensional field theory, and was used in scalar theories and QED. In this article this method is generalized to more complicated models by direct calculation of generating functions on a computer algebra system. This method is applied to QCD with and without counter terms, where many higher order are being calculated automatically.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Volkov, S. A., E-mail: volkoff-sergey@mail.ru
2016-06-15
A new subtractive procedure for canceling ultraviolet and infrared divergences in the Feynman integrals described here is developed for calculating QED corrections to the electron anomalous magnetic moment. The procedure formulated in the form of a forest expression with linear operators applied to Feynman amplitudes of UV-diverging subgraphs makes it possible to represent the contribution of each Feynman graph containing only electron and photon propagators in the form of a converging integral with respect to Feynman parameters. The application of the developed method for numerical calculation of two- and threeloop contributions is described.
Thinking in Pictures: John Wheeler, Richard Feynman and the Diagrammatic Approach to Problem Solving
NASA Astrophysics Data System (ADS)
Halpern, Paul
While classical mechanics readily lends itself to sketches, many fields of modern physics, particularly quantum mechanics, quantum field theory, and general relativity, are notoriously hard to envision. Nevertheless, John Wheeler and Richard Feynman, who obtained his PhD under Wheeler, each insisted that diagrams were the most effective way to tackle modern physics questions as well. Beginning with Wheeler and Feynman's work together at Princeton, I'll show how the two influenced each other and encouraged each other's diagrammatic methods. I'll explore the influence on Feynman of not just Wheeler, but also of his first wife Arline, an aspiring artist. I'll describe how Feynman diagrams, introduced in the late 1940s, while first seen as `heretical' in the face of Bohr's complementarity, became standard, essential methods. I'll detail Wheeler's encouragement of his colleague Martin Kruskal's use of special diagrams to elucidate the properties of black holes. Finally, I'll show how each physicist supported art later in life: Wheeler helping to arrange the Putnam Collection of 20th century sculpture at Princeton and Feynman, in a kind of `second career,' becoming an artist himself.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Choi, Jae Gil, E-mail: jgchoi@dankook.ac.kr; Chang, Seung Jun, E-mail: sejchang@dankook.ac.kr
In this paper we derive a Cameron-Storvick theorem for the analytic Feynman integral of functionals on product abstract Wiener space B{sup 2}. We then apply our result to obtain an evaluation formula for the analytic Feynman integral of unbounded functionals on B{sup 2}. We also present meaningful examples involving functionals which arise naturally in quantum mechanics.
On the Path Integral in Non-Commutative (nc) Qft
NASA Astrophysics Data System (ADS)
Dehne, Christoph
2008-09-01
As is generally known, different quantization schemes applied to field theory on NC spacetime lead to Feynman rules with different physical properties, if time does not commute with space. In particular, the Feynman rules that are derived from the path integral corresponding to the T*-product (the so-called naïve Feynman rules) violate the causal time ordering property. Within the Hamiltonian approach to quantum field theory, we show that we can (formally) modify the time ordering encoded in the above path integral. The resulting Feynman rules are identical to those obtained in the canonical approach via the Gell-Mann-Low formula (with T-ordering). They preserve thus unitarity and causal time ordering.
Integrand Reduction Reloaded: Algebraic Geometry and Finite Fields
NASA Astrophysics Data System (ADS)
Sameshima, Ray D.; Ferroglia, Andrea; Ossola, Giovanni
2017-01-01
The evaluation of scattering amplitudes in quantum field theory allows us to compare the phenomenological prediction of particle theory with the measurement at collider experiments. The study of scattering amplitudes, in terms of their symmetries and analytic properties, provides a theoretical framework to develop techniques and efficient algorithms for the evaluation of physical cross sections and differential distributions. Tree-level calculations have been known for a long time. Loop amplitudes, which are needed to reduce the theoretical uncertainty, are more challenging since they involve a large number of Feynman diagrams, expressed as integrals of rational functions. At one-loop, the problem has been solved thanks to the combined effect of integrand reduction, such as the OPP method, and unitarity. However, plenty of work is still needed at higher orders, starting with the two-loop case. Recently, integrand reduction has been revisited using algebraic geometry. In this presentation, we review the salient features of integrand reduction for dimensionally regulated Feynman integrals, and describe an interesting technique for their reduction based on multivariate polynomial division. We also show a novel approach to improve its efficiency by introducing finite fields. Supported in part by the National Science Foundation under Grant PHY-1417354.
NASA Astrophysics Data System (ADS)
Fan, Hong-yi; Xu, Xue-xiang
2009-06-01
By virtue of the generalized Hellmann-Feynman theorem [H. Y. Fan and B. Z. Chen, Phys. Lett. A 203, 95 (1995)], we derive the mean energy of some interacting bosonic systems for some Hamiltonian models without proceeding with diagonalizing the Hamiltonians. Our work extends the field of applications of the Hellmann-Feynman theorem and may enrich the theory of quantum statistics.
The ε-form of the differential equations for Feynman integrals in the elliptic case
NASA Astrophysics Data System (ADS)
Adams, Luise; Weinzierl, Stefan
2018-06-01
Feynman integrals are easily solved if their system of differential equations is in ε-form. In this letter we show by the explicit example of the kite integral family that an ε-form can even be achieved, if the Feynman integrals do not evaluate to multiple polylogarithms. The ε-form is obtained by a (non-algebraic) change of basis for the master integrals.
Quantum many-body effects in x-ray spectra efficiently computed using a basic graph algorithm
NASA Astrophysics Data System (ADS)
Liang, Yufeng; Prendergast, David
2018-05-01
The growing interest in using x-ray spectroscopy for refined materials characterization calls for an accurate electronic-structure theory to interpret the x-ray near-edge fine structure. In this work, we propose an efficient and unified framework to describe all the many-electron processes in a Fermi liquid after a sudden perturbation (such as a core hole). This problem has been visited by the Mahan-Noziéres-De Dominicis (MND) theory, but it is intractable to implement various Feynman diagrams within first-principles calculations. Here, we adopt a nondiagrammatic approach and treat all the many-electron processes in the MND theory on an equal footing. Starting from a recently introduced determinant formalism [Phys. Rev. Lett. 118, 096402 (2017), 10.1103/PhysRevLett.118.096402], we exploit the linear dependence of determinants describing different final states involved in the spectral calculations. An elementary graph algorithm, breadth-first search, can be used to quickly identify the important determinants for shaping the spectrum, which avoids the need to evaluate a great number of vanishingly small terms. This search algorithm is performed over the tree-structure of the many-body expansion, which mimics a path-finding process. We demonstrate that the determinantal approach is computationally inexpensive even for obtaining x-ray spectra of extended systems. Using Kohn-Sham orbitals from two self-consistent fields (ground and core-excited state) as input for constructing the determinants, the calculated x-ray spectra for a number of transition metal oxides are in good agreement with experiments. Many-electron aspects beyond the Bethe-Salpeter equation, as captured by this approach, are also discussed, such as shakeup excitations and many-body wave function overlap considered in Anderson's orthogonality catastrophe.
Free field theory as a string theory?
NASA Astrophysics Data System (ADS)
Gopakumar, Rajesh
2004-11-01
An approach to systematically implement open-closed string duality for free large N gauge theories is summarised. We show how the relevant closed string moduli space emerges from a reorganisation of the Feynman diagrams contributing to free field correlators. We also indicate why the resulting integrand on moduli space has the right features to be that of a string theory on AdS. To cite this article: R. Gopakumar, C. R. Physique 5 (2004).
NASA Astrophysics Data System (ADS)
Castro, E.
2018-02-01
From the perturbative expansion of the exact Green function, an exact counting formula is derived to determine the number of different types of connected Feynman diagrams. This formula coincides with the Arquès-Walsh sequence formula in the rooted map theory, supporting the topological connection between Feynman diagrams and rooted maps. A classificatory summing-terms approach is used, in connection to discrete mathematical theory.
A Representation for Fermionic Correlation Functions
NASA Astrophysics Data System (ADS)
Feldman, Joel; Knörrer, Horst; Trubowitz, Eugene
Let dμS(a) be a Gaussian measure on the finitely generated Grassmann algebra A. Given an even W(a)∈A, we construct an operator R on A such that
A Staged Reading of the Play: Moving Bodies
NASA Astrophysics Data System (ADS)
Schwartz, Brian
Moving Bodies is about Nobel Prize-winning physicist Richard Feynman as he explores nature, science, sex, anti-Semitism, and the world around him. This epic, comic journey portrays Feynman as an iconoclastic young man, a physicist with the Manhattan Project and confronting the mystery of the Challenger disaster. The Atomic Bomb is central to the play, but it is also very much about human loves and losses. We learn about his (Feynman's) eccentricities: his bongo playing, his penchant for picking locks, and most notably his appreciation for women. Through playwright Arthur Giron's eyes, we see how Feynman became one of the most important scientists of our time. The playwright, Arthur Giron, is the co-playwright of the recent 2015 Broadway Musical, Amazing Grace. The staged reading is performed by the Southern Rep Theatre. http://www.southernrep.com/ The play director and actors as well as a historian-scientist who knew Feynman will be available for a talk-back discussion after the play reading. Produced by Brian Schwartz, CUNY and Gregory Mack, APS. Sponsored by: The Forum on the History of Physics, The Forum on Outreach and Engaging the Public and The Forum on Physics and Society.
Feynman rules for a whole Abelian model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chauca, J.; Doria, R.; Soares, W.
2012-09-24
Feynman rules for an abelian extension of gauge theories are discussed and explicitly derived. Vertices with three and four abelian gauge bosons are obtained. A discussion on an eventual structure for the photon is presented.
Opening the Pandora's box of quantum spinor fields
NASA Astrophysics Data System (ADS)
Bonora, L.; Silva, J. M. Hoff da; Rocha, R. da
2018-02-01
Lounesto's classification of spinors is a comprehensive and exhaustive algorithm that, based on the bilinears covariants, discloses the possibility of a large variety of spinors, comprising regular and singular spinors and their unexpected applications in physics and including the cases of Dirac, Weyl, and Majorana as very particular spinor fields. In this paper we pose the problem of an analogous classification in the framework of second quantization. We first discuss in general the nature of the problem. Then we start the analysis of two basic bilinear covariants, the scalar and pseudoscalar, in the second quantized setup, with expressions applicable to the quantum field theory extended to all types of spinors. One can see that an ampler set of possibilities opens up with respect to the classical case. A quantum reconstruction algorithm is also proposed. The Feynman propagator is extended for spinors in all classes.
Particles, Feynman Diagrams and All That
ERIC Educational Resources Information Center
Daniel, Michael
2006-01-01
Quantum fields are introduced in order to give students an accurate qualitative understanding of the origin of Feynman diagrams as representations of particle interactions. Elementary diagrams are combined to produce diagrams representing the main features of the Standard Model.
Richard P. Feynman and the Feynman Diagrams
available in full-text and on the Web. Documents: A Theorem and Its Application to Finite Tampers, DOE Fermi-Thomas Theory; DOE Technical Report, April 28, 1947 Mathematical Formulation of the Quantum Theory
Probing finite coarse-grained virtual Feynman histories with sequential weak values
NASA Astrophysics Data System (ADS)
Georgiev, Danko; Cohen, Eliahu
2018-05-01
Feynman's sum-over-histories formulation of quantum mechanics has been considered a useful calculational tool in which virtual Feynman histories entering into a coherent quantum superposition cannot be individually measured. Here we show that sequential weak values, inferred by consecutive weak measurements of projectors, allow direct experimental probing of individual virtual Feynman histories, thereby revealing the exact nature of quantum interference of coherently superposed histories. Because the total sum of sequential weak values of multitime projection operators for a complete set of orthogonal quantum histories is unity, complete sets of weak values could be interpreted in agreement with the standard quantum mechanical picture. We also elucidate the relationship between sequential weak values of quantum histories with different coarse graining in time and establish the incompatibility of weak values for nonorthogonal quantum histories in history Hilbert space. Bridging theory and experiment, the presented results may enhance our understanding of both weak values and quantum histories.
Feynman-Kac formula for stochastic hybrid systems.
Bressloff, Paul C
2017-01-01
We derive a Feynman-Kac formula for functionals of a stochastic hybrid system evolving according to a piecewise deterministic Markov process. We first derive a stochastic Liouville equation for the moment generator of the stochastic functional, given a particular realization of the underlying discrete Markov process; the latter generates transitions between different dynamical equations for the continuous process. We then analyze the stochastic Liouville equation using methods recently developed for diffusion processes in randomly switching environments. In particular, we obtain dynamical equations for the moment generating function, averaged with respect to realizations of the discrete Markov process. The resulting Feynman-Kac formula takes the form of a differential Chapman-Kolmogorov equation. We illustrate the theory by calculating the occupation time for a one-dimensional velocity jump process on the infinite or semi-infinite real line. Finally, we present an alternative derivation of the Feynman-Kac formula based on a recent path-integral formulation of stochastic hybrid systems.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Perkins, R. J., E-mail: rperkins@pppl.gov; Bellan, P. M.
Action integrals are often used to average a system over fast oscillations and obtain reduced dynamics. It is not surprising, then, that action integrals play a central role in the Hellmann-Feynman theorem of classical mechanics, which furnishes the values of certain quantities averaged over one period of rapid oscillation. This paper revisits the classical Hellmann-Feynman theorem, rederiving it in connection to an analogous theorem involving the time-averaged evolution of canonical coordinates. We then apply a modified version of the Hellmann-Feynman theorem to obtain a new result: the magnetic flux enclosed by one period of gyro-motion of a charged particle inmore » a non-uniform magnetic field. These results further demonstrate the utility of the action integral in regards to obtaining orbit-averaged quantities and the usefulness of this formalism in characterizing charged particle motion.« less
Quantum theory of multiscale coarse-graining.
Han, Yining; Jin, Jaehyeok; Wagner, Jacob W; Voth, Gregory A
2018-03-14
Coarse-grained (CG) models serve as a powerful tool to simulate molecular systems at much longer temporal and spatial scales. Previously, CG models and methods have been built upon classical statistical mechanics. The present paper develops a theory and numerical methodology for coarse-graining in quantum statistical mechanics, by generalizing the multiscale coarse-graining (MS-CG) method to quantum Boltzmann statistics. A rigorous derivation of the sufficient thermodynamic consistency condition is first presented via imaginary time Feynman path integrals. It identifies the optimal choice of CG action functional and effective quantum CG (qCG) force field to generate a quantum MS-CG (qMS-CG) description of the equilibrium system that is consistent with the quantum fine-grained model projected onto the CG variables. A variational principle then provides a class of algorithms for optimally approximating the qMS-CG force fields. Specifically, a variational method based on force matching, which was also adopted in the classical MS-CG theory, is generalized to quantum Boltzmann statistics. The qMS-CG numerical algorithms and practical issues in implementing this variational minimization procedure are also discussed. Then, two numerical examples are presented to demonstrate the method. Finally, as an alternative strategy, a quasi-classical approximation for the thermal density matrix expressed in the CG variables is derived. This approach provides an interesting physical picture for coarse-graining in quantum Boltzmann statistical mechanics in which the consistency with the quantum particle delocalization is obviously manifest, and it opens up an avenue for using path integral centroid-based effective classical force fields in a coarse-graining methodology.
A global solution to the Schrödinger equation: From Henstock to Feynman
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nathanson, Ekaterina S., E-mail: enathanson@ggc.edu; Jørgensen, Palle E. T., E-mail: palle-jorgensen@uiowa.edu
2015-09-15
One of the key elements of Feynman’s formulation of non-relativistic quantum mechanics is a so-called Feynman path integral. It plays an important role in the theory, but it appears as a postulate based on intuition, rather than a well-defined object. All previous attempts to supply Feynman’s theory with rigorous mathematics underpinning, based on the physical requirements, have not been satisfactory. The difficulty comes from the need to define a measure on the infinite dimensional space of paths and to create an integral that would possess all of the properties requested by Feynman. In the present paper, we consider a newmore » approach to defining the Feynman path integral, based on the theory developed by Muldowney [A Modern Theory of Random Variable: With Applications in Stochastic Calcolus, Financial Mathematics, and Feynman Integration (John Wiley & Sons, Inc., New Jersey, 2012)]. Muldowney uses the Henstock integration technique and deals with non-absolute integrability of the Fresnel integrals, in order to obtain a representation of the Feynman path integral as a functional. This approach offers a mathematically rigorous definition supporting Feynman’s intuitive derivations. But in his work, Muldowney gives only local in space-time solutions. A physical solution to the non-relativistic Schrödinger equation must be global, and it must be given in the form of a unitary one-parameter group in L{sup 2}(ℝ{sup n}). The purpose of this paper is to show that a system of one-dimensional local Muldowney’s solutions may be extended to yield a global solution. Moreover, the global extension can be represented by a unitary one-parameter group acting in L{sup 2}(ℝ{sup n})« less
Search Site submit About Us Los Alamos National LaboratoryRichard P. Feynman Center for Innovation Innovation protecting tomorrow Los Alamos National Laboratory The Richard P. Feynman Center for Innovation . thumbnail of Energy and Subsurface Laura Barber, Business Development Laura Barber Energy: Los Alamos is
Search Site submit About Us Los Alamos National LaboratoryRichard P. Feynman Center for Innovation Innovation protecting tomorrow Los Alamos National Laboratory The Richard P. Feynman Center for Innovation key programs to achieve regional technology commercialization from Los Alamos. The programs below help
Huygens-Feynman-Fresnel principle as the basis of applied optics.
Gitin, Andrey V
2013-11-01
The main relationships of wave optics are derived from a combination of the Huygens-Fresnel principle and the Feynman integral over all paths. The stationary-phase approximation of the wave relations gives the correspondent relations from the point of view of geometrical optics.
The signed permutation group on Feynman graphs
DOE Office of Scientific and Technical Information (OSTI.GOV)
Purkart, Julian, E-mail: purkart@physik.hu-berlin.de
2016-08-15
The Feynman rules assign to every graph an integral which can be written as a function of a scaling parameter L. Assuming L for the process under consideration is very small, so that contributions to the renormalization group are small, we can expand the integral and only consider the lowest orders in the scaling. The aim of this article is to determine specific combinations of graphs in a scalar quantum field theory that lead to a remarkable simplification of the first non-trivial term in the perturbation series. It will be seen that the result is independent of the renormalization schememore » and the scattering angles. To achieve that goal we will utilize the parametric representation of scalar Feynman integrals as well as the Hopf algebraic structure of the Feynman graphs under consideration. Moreover, we will present a formula which reduces the effort of determining the first-order term in the perturbation series for the specific combination of graphs to a minimum.« less
Navigating around the algebraic jungle of QCD: efficient evaluation of loop helicity amplitudes
NASA Astrophysics Data System (ADS)
Lam, C. S.
1993-05-01
A method is developed whereby spinor helicity techniques can be used to simlify the calculation of loop amplitudes. This is achieved by using the Feynman-parameter representation where the offending off-shell loop momenta do not appear. Other shortcuts motivated by the Bern-Kosower one-loop string calculations can be incorporated into the formalism. This includes color reorganization into Chan-Paton factors and the use of background Feynman gauge. This method is applicable to any Feynman diagram with any number of loops as long as the external masses can be ignored. In order to minimize the very considerable algebra encountered in non-abelian gauge theories, graphical methods are developed for most of the calculations. This enables the large number of terms encountered to be organized implicitly in the Feynman diagram without the necessity of writing down any of them algebraically. A one-loop four-gluon amplitude in a particular helicity configuration is computed explicitly to illustrate the method.
Computer Simulation of Electron Positron Annihilation Processes
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, y
2003-10-02
With the launching of the Next Linear Collider coming closer and closer, there is a pressing need for physicists to develop a fully-integrated computer simulation of e{sup +}e{sup -} annihilation process at center-of-mass energy of 1TeV. A simulation program acts as the template for future experiments. Either new physics will be discovered, or current theoretical uncertainties will shrink due to more accurate higher-order radiative correction calculations. The existence of an efficient and accurate simulation will help us understand the new data and validate (or veto) some of the theoretical models developed to explain new physics. It should handle well interfacesmore » between different sectors of physics, e.g., interactions happening at parton levels well above the QCD scale which are described by perturbative QCD, and interactions happening at much lower energy scale, which combine partons into hadrons. Also it should achieve competitive speed in real time when the complexity of the simulation increases. This thesis contributes some tools that will be useful for the development of such simulation programs. We begin our study by the development of a new Monte Carlo algorithm intended to perform efficiently in selecting weight-1 events when multiple parameter dimensions are strongly correlated. The algorithm first seeks to model the peaks of the distribution by features, adapting these features to the function using the EM algorithm. The representation of the distribution provided by these features is then improved using the VEGAS algorithm for the Monte Carlo integration. The two strategies mesh neatly into an effective multi-channel adaptive representation. We then present a new algorithm for the simulation of parton shower processes in high energy QCD. We want to find an algorithm which is free of negative weights, produces its output as a set of exclusive events, and whose total rate exactly matches the full Feynman amplitude calculation. Our strategy is to create the whole QCD shower as a tree structure generated by a multiple Poisson process. Working with the whole shower allows us to include correlations between gluon emissions from different sources. QCD destructive interference is controlled by the implementation of ''angular-ordering,'' as in the HERWIG Monte Carlo program. We discuss methods for systematic improvement of the approach to include higher order QCD effects.« less
Quantum walks in brain microtubules--a biomolecular basis for quantum cognition?
Hameroff, Stuart
2014-01-01
Cognitive decisions are best described by quantum mathematics. Do quantum information devices operate in the brain? What would they look like? Fuss and Navarro () describe quantum lattice registers in which quantum superpositioned pathways interact (compute/integrate) as 'quantum walks' akin to Feynman's path integral in a lattice (e.g. the 'Feynman quantum chessboard'). Simultaneous alternate pathways eventually reduce (collapse), selecting one particular pathway in a cognitive decision, or choice. This paper describes how quantum walks in a Feynman chessboard are conceptually identical to 'topological qubits' in brain neuronal microtubules, as described in the Penrose-Hameroff 'Orch OR' theory of consciousness. Copyright © 2013 Cognitive Science Society, Inc.
Application of the Feynman-tree theorem together with BCFW recursion relations
NASA Astrophysics Data System (ADS)
Maniatis, M.
2018-03-01
Recently, it has been shown that on-shell scattering amplitudes can be constructed by the Feynman-tree theorem combined with the BCFW recursion relations. Since the BCFW relations are restricted to tree diagrams, the preceding application of the Feynman-tree theorem is essential. In this way, amplitudes can be constructed by on-shell and gauge-invariant tree amplitudes. Here, we want to apply this method to the electron-photon vertex correction. We present all the single, double, and triple phase-space tensor integrals explicitly and show that the sum of amplitudes coincides with the result of the conventional calculation of a virtual loop correction.
Exact Maximum-Entropy Estimation with Feynman Diagrams
NASA Astrophysics Data System (ADS)
Netser Zernik, Amitai; Schlank, Tomer M.; Tessler, Ran J.
2018-02-01
A longstanding open problem in statistics is finding an explicit expression for the probability measure which maximizes entropy with respect to given constraints. In this paper a solution to this problem is found, using perturbative Feynman calculus. The explicit expression is given as a sum over weighted trees.
Teaching Basic Quantum Mechanics in Secondary School Using Concepts of Feynman Path Integrals Method
ERIC Educational Resources Information Center
Fanaro, Maria de los Angeles; Otero, Maria Rita; Arlego, Marcelo
2012-01-01
This paper discusses the teaching of basic quantum mechanics in high school. Rather than following the usual formalism, our approach is based on Feynman's path integral method. Our presentation makes use of simulation software and avoids sophisticated mathematical formalism. (Contains 3 figures.)
Nanotechnology: From Feynman to Funding
ERIC Educational Resources Information Center
Drexler, K. Eric
2004-01-01
The revolutionary Feynman vision of a powerful and general nanotechnology, based on nanomachines that build with atom-by-atom control, promises great opportunities and, if abused, great dangers. This vision made nanotechnology a buzzword and launched the global nanotechnology race. Along the way, however, the meaning of the word has shifted. A…
Implications of improved Higgs mass calculations for supersymmetric models.
Buchmueller, O; Dolan, M J; Ellis, J; Hahn, T; Heinemeyer, S; Hollik, W; Marrouche, J; Olive, K A; Rzehak, H; de Vries, K J; Weiglein, G
We discuss the allowed parameter spaces of supersymmetric scenarios in light of improved Higgs mass predictions provided by FeynHiggs 2.10.0. The Higgs mass predictions combine Feynman-diagrammatic results with a resummation of leading and subleading logarithmic corrections from the stop/top sector, which yield a significant improvement in the region of large stop masses. Scans in the pMSSM parameter space show that, for given values of the soft supersymmetry-breaking parameters, the new logarithmic contributions beyond the two-loop order implemented in FeynHiggs tend to give larger values of the light CP-even Higgs mass, [Formula: see text], in the region of large stop masses than previous predictions that were based on a fixed-order Feynman-diagrammatic result, though the differences are generally consistent with the previous estimates of theoretical uncertainties. We re-analyse the parameter spaces of the CMSSM, NUHM1 and NUHM2, taking into account also the constraints from CMS and LHCb measurements of [Formula: see text]and ATLAS searches for [Formula: see text] events using 20/fb of LHC data at 8 TeV. Within the CMSSM, the Higgs mass constraint disfavours [Formula: see text], though not in the NUHM1 or NUHM2.
Computing exponentially faster: implementing a non-deterministic universal Turing machine using DNA
Currin, Andrew; Korovin, Konstantin; Ababi, Maria; Roper, Katherine; Kell, Douglas B.; Day, Philip J.
2017-01-01
The theory of computer science is based around universal Turing machines (UTMs): abstract machines able to execute all possible algorithms. Modern digital computers are physical embodiments of classical UTMs. For the most important class of problem in computer science, non-deterministic polynomial complete problems, non-deterministic UTMs (NUTMs) are theoretically exponentially faster than both classical UTMs and quantum mechanical UTMs (QUTMs). However, no attempt has previously been made to build an NUTM, and their construction has been regarded as impossible. Here, we demonstrate the first physical design of an NUTM. This design is based on Thue string rewriting systems, and thereby avoids the limitations of most previous DNA computing schemes: all the computation is local (simple edits to strings) so there is no need for communication, and there is no need to order operations. The design exploits DNA's ability to replicate to execute an exponential number of computational paths in P time. Each Thue rewriting step is embodied in a DNA edit implemented using a novel combination of polymerase chain reactions and site-directed mutagenesis. We demonstrate that the design works using both computational modelling and in vitro molecular biology experimentation: the design is thermodynamically favourable, microprogramming can be used to encode arbitrary Thue rules, all classes of Thue rule can be implemented, and non-deterministic rule implementation. In an NUTM, the resource limitation is space, which contrasts with classical UTMs and QUTMs where it is time. This fundamental difference enables an NUTM to trade space for time, which is significant for both theoretical computer science and physics. It is also of practical importance, for to quote Richard Feynman ‘there's plenty of room at the bottom’. This means that a desktop DNA NUTM could potentially utilize more processors than all the electronic computers in the world combined, and thereby outperform the world's current fastest supercomputer, while consuming a tiny fraction of its energy. PMID:28250099
Feynman-Kac equations for reaction and diffusion processes
NASA Astrophysics Data System (ADS)
Hou, Ru; Deng, Weihua
2018-04-01
This paper provides a theoretical framework for deriving the forward and backward Feynman-Kac equations for the distribution of functionals of the path of a particle undergoing both diffusion and reaction processes. Once given the diffusion type and reaction rate, a specific forward or backward Feynman-Kac equation can be obtained. The results in this paper include those for normal/anomalous diffusions and reactions with linear/nonlinear rates. Using the derived equations, we apply our findings to compute some physical (experimentally measurable) statistics, including the occupation time in half-space, the first passage time, and the occupation time in half-interval with an absorbing or reflecting boundary, for the physical system with anomalous diffusion and spontaneous evanescence.
From Loops to Trees By-passing Feynman's Theorem
DOE Office of Scientific and Technical Information (OSTI.GOV)
Catani, Stefano; Gleisberg, Tanju; Krauss, Frank
2008-04-22
We derive a duality relation between one-loop integrals and phase-space integrals emerging from them through single cuts. The duality relation is realized by a modification of the customary + i0 prescription of the Feynman propagators. The new prescription regularizing the propagators, which we write in a Lorentz covariant form, compensates for the absence of multiple cut contributions that appear in the Feynman Tree Theorem. The duality relation can be applied to generic one-loop quantities in any relativistic, local and unitary field theories. It is suitable for applications to the analytical calculation of one-loop scattering amplitudes, and to the numerical evaluationmore » of cross-sections at next-to-leading order.« less
General consequences of the violated Feynman scaling
NASA Technical Reports Server (NTRS)
Kamberov, G.; Popova, L.
1985-01-01
The problem of scaling of the hadronic production cross sections represents an outstanding question in high energy physics especially for interpretation of cosmic ray data. A comprehensive analysis of the accelerator data leads to the conclusion of the existence of breaked Feynman scaling. It was proposed that the Lorentz invariant inclusive cross sections for secondaries of a given type approaches constant in respect to a breaked scaling variable x sub s. Thus, the differential cross sections measured in accelerator energy can be extrapolated to higher cosmic ray energies. This assumption leads to some important consequences. The distribution of secondary multiplicity that follows from the violated Feynman scaling using a similar method of Koba et al is discussed.
The Pleasure of Finding Things out
ERIC Educational Resources Information Center
Loxley, Peter
2005-01-01
"The pleasure of finding things out" is a collection of short works by the Nobel Prize winning scientist Richard Feynman. The book provides insights into his infectious enthusiasm for science and his love of sharing ideas about the subject with anyone who wanted to listen. Feynman has been widely acknowledged as one of the greatest physicists of…
The static hard-loop gluon propagator to all orders in anisotropy
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nopoush, Mohammad; Guo, Yun; Strickland, Michael
We calculate the (semi-)static hard-loop self-energy and propagator using the Keldysh formalism in a momentum-space anisotropic quark-gluon plasma. The static retarded, advanced, and Feynman (symmetric) self-energies and propagators are calculated to all orders in the momentum-space anisotropy parameter ξ. For the retarded and advanced self-energies/propagators, we present a concise derivation and comparison with previouslyobtained results and extend the calculation of the self-energies to next-to-leading order in the gluon energy, ω. For the Feynman self-energy/propagator, we present new results which are accurate to all orders in ξ. We compare our exact results with prior expressions for the Feynman self-energy/propagator which weremore » obtained using Taylor-expansions around an isotropic state. Here, we show that, unlike the Taylor-expanded results, the all-orders expression for the Feynman propagator is free from infrared singularities. Finally, we discuss the application of our results to the calculation of the imaginary-part of the heavy-quark potential in an anisotropic quark-gluon plasma.« less
Feynman-like rules for calculating n-point correlators of the primordial curvature perturbation
NASA Astrophysics Data System (ADS)
Valenzuela-Toledo, César A.; Rodríguez, Yeinzon; Beltrán Almeida, Juan P.
2011-10-01
A diagrammatic approach to calculate n-point correlators of the primordial curvature perturbation ζ was developed a few years ago following the spirit of the Feynman rules in Quantum Field Theory. The methodology is very useful and time-saving, as it is for the case of the Feynman rules in the particle physics context, but, unfortunately, is not very well known by the cosmology community. In the present work, we extend such an approach in order to include not only scalar field perturbations as the generators of ζ, but also vector field perturbations. The purpose is twofold: first, we would like the diagrammatic approach (which we would call the Feynman-like rules) to become widespread among the cosmology community; second, we intend to give an easy tool to formulate any correlator of ζ for those cases that involve vector field perturbations and that, therefore, may generate prolonged stages of anisotropic expansion and/or important levels of statistical anisotropy. Indeed, the usual way of formulating such correlators, using the Wick's theorem, may become very clutter and time-consuming.
Feynman formulas for semigroups generated by an iterated Laplace operator
NASA Astrophysics Data System (ADS)
Buzinov, M. S.
2017-04-01
In the present paper, we find representations of a one-parameter semigroup generated by a finite sum of iterated Laplace operators and an additive perturbation (the potential). Such semigroups and the evolution equations corresponding to them find applications in the field of physics, chemistry, biology, and pattern recognition. The representations mentioned above are obtained in the form of Feynman formulas, i.e., in the form of a limit of multiple integrals as the multiplicity tends to infinity. The term "Feynman formula" was proposed by Smolyanov. Smolyanov's approach uses Chernoff's theorems. A simple form of representations thus obtained enables one to use them for numerical modeling the dynamics of the evolution system as a method for the approximation of solutions of equations. The problems considered in this note can be treated using the approach suggested by Remizov (see also the monograph of Smolyanov and Shavgulidze on path integrals). The representations (of semigroups) obtained in this way are more complicated than those given by the Feynman formulas; however, it is possible to bypass some analytical difficulties.
The static hard-loop gluon propagator to all orders in anisotropy
Nopoush, Mohammad; Guo, Yun; Strickland, Michael
2017-09-15
We calculate the (semi-)static hard-loop self-energy and propagator using the Keldysh formalism in a momentum-space anisotropic quark-gluon plasma. The static retarded, advanced, and Feynman (symmetric) self-energies and propagators are calculated to all orders in the momentum-space anisotropy parameter ξ. For the retarded and advanced self-energies/propagators, we present a concise derivation and comparison with previouslyobtained results and extend the calculation of the self-energies to next-to-leading order in the gluon energy, ω. For the Feynman self-energy/propagator, we present new results which are accurate to all orders in ξ. We compare our exact results with prior expressions for the Feynman self-energy/propagator which weremore » obtained using Taylor-expansions around an isotropic state. Here, we show that, unlike the Taylor-expanded results, the all-orders expression for the Feynman propagator is free from infrared singularities. Finally, we discuss the application of our results to the calculation of the imaginary-part of the heavy-quark potential in an anisotropic quark-gluon plasma.« less
On the Presentation of Wave Phenomena of Electrons with the Young-Feynman Experiment
ERIC Educational Resources Information Center
Matteucci, Giorgio
2011-01-01
The Young-Feynman two-hole interferometer is widely used to present electron wave-particle duality and, in particular, the buildup of interference fringes with single electrons. The teaching approach consists of two steps: (i) electrons come through only one hole but diffraction effects are disregarded and (ii) electrons come through both holes…
Teaching Electron--Positron--Photon Interactions with Hands-on Feynman Diagrams
ERIC Educational Resources Information Center
Kontokostas, George; Kalkanis, George
2013-01-01
Feynman diagrams are introduced in many physics textbooks, such as those by Alonso and Finn and Serway, and their use in physics education has been discussed by various authors. They have an appealing simplicity and can give insight into events in the microworld. Yet students often do not understand their significance and often cannot combine the…
ERIC Educational Resources Information Center
Pascolini, A.; Pietroni, M.
2002-01-01
We report on an educational project in particle physics based on Feynman diagrams. By dropping the mathematical aspect of the method and keeping just the iconic one, it is possible to convey many different concepts from the world of elementary particles, such as antimatter, conservation laws, particle creation and destruction, real and virtual…
NASA Astrophysics Data System (ADS)
Chernikova, Dina; Axell, Kåre; Avdic, Senada; Pázsit, Imre; Nordlund, Anders; Allard, Stefan
2015-05-01
Two versions of the neutron-gamma variance to mean (Feynman-alpha method or Feynman-Y function) formula for either gamma detection only or total neutron-gamma detection, respectively, are derived and compared in this paper. The new formulas have particular importance for detectors of either gamma photons or detectors sensitive to both neutron and gamma radiation. If applied to a plastic or liquid scintillation detector, the total neutron-gamma detection Feynman-Y expression corresponds to a situation where no discrimination is made between neutrons and gamma particles. The gamma variance to mean formulas are useful when a detector of only gamma radiation is used or when working with a combined neutron-gamma detector at high count rates. The theoretical derivation is based on the Chapman-Kolmogorov equation with the inclusion of general reactions and corresponding intensities for neutrons and gammas, but with the inclusion of prompt reactions only. A one energy group approximation is considered. The comparison of the two different theories is made by using reaction intensities obtained in MCNPX simulations with a simplified geometry for two scintillation detectors and a 252Cf-source. In addition, the variance to mean ratios, neutron, gamma and total neutron-gamma are evaluated experimentally for a weak 252Cf neutron-gamma source, a 137Cs random gamma source and a 22Na correlated gamma source. Due to the focus being on the possibility of using neutron-gamma variance to mean theories for both reactor and safeguards applications, we limited the present study to the general analytical expressions for Feynman-alpha formulas.
ERIC Educational Resources Information Center
Onorato, P.
2011-01-01
An introduction to quantum mechanics based on the sum-over-paths (SOP) method originated by Richard P. Feynman and developed by E. F. Taylor and coworkers is presented. The Einstein-Brillouin-Keller (EBK) semiclassical quantization rules are obtained following the SOP approach for bounded systems, and a general approach to the calculation of…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Flego, S.P.; Plastino, A.; Universitat de les Illes Balears and IFISC-CSIC, 07122 Palma de Mallorca
We explore intriguing links connecting Hellmann-Feynman's theorem to a thermodynamics information-optimizing principle based on Fisher's information measure. - Highlights: > We link a purely quantum mechanical result, the Hellmann-Feynman theorem, with Jaynes' information theoretical reciprocity relations. > These relations involve the coefficients of a series expansion of the potential function. > We suggest the existence of a Legendre transform structure behind Schroedinger's equation, akin to the one characterizing thermodynamics.
Feynman amplitudes and limits of heights
NASA Astrophysics Data System (ADS)
Amini, O.; Bloch, S. J.; Burgos Gil, J. I.; Fresán, J.
2016-10-01
We investigate from a mathematical perspective how Feynman amplitudes appear in the low-energy limit of string amplitudes. In this paper, we prove the convergence of the integrands. We derive this from results describing the asymptotic behaviour of the height pairing between degree-zero divisors, as a family of curves degenerates. These are obtained by means of the nilpotent orbit theorem in Hodge theory.
ERIC Educational Resources Information Center
Field, J. H.
2011-01-01
It is shown how the time-dependent Schrodinger equation may be simply derived from the dynamical postulate of Feynman's path integral formulation of quantum mechanics and the Hamilton-Jacobi equation of classical mechanics. Schrodinger's own published derivations of quantum wave equations, the first of which was also based on the Hamilton-Jacobi…
Importance sampling studies of helium using the Feynman-Kac path integral method
NASA Astrophysics Data System (ADS)
Datta, S.; Rejcek, J. M.
2018-05-01
In the Feynman-Kac path integral approach the eigenvalues of a quantum system can be computed using Wiener measure which uses Brownian particle motion. In our previous work on such systems we have observed that the Wiener process numerically converges slowly for dimensions greater than two because almost all trajectories will escape to infinity. One can speed up this process by using a generalized Feynman-Kac (GFK) method, in which the new measure associated with the trial function is stationary, so that the convergence rate becomes much faster. We thus achieve an example of "importance sampling" and, in the present work, we apply it to the Feynman-Kac (FK) path integrals for the ground and first few excited-state energies for He to speed up the convergence rate. We calculate the path integrals using space averaging rather than the time averaging as done in the past. The best previous calculations from variational computations report precisions of 10-16 Hartrees, whereas in most cases our path integral results obtained for the ground and first excited states of He are lower than these results by about 10-6 Hartrees or more.
Coupled oscillators and Feynman's three papers
NASA Astrophysics Data System (ADS)
Kim, Y. S.
2007-05-01
According to Richard Feynman, the adventure of our science of physics is a perpetual attempt to recognize that the different aspects of nature are really different aspects of the same thing. It is therefore interesting to combine some, if not all, of Feynman's papers into one. The first of his three papers is on the "rest of the universe" contained in his 1972 book on statistical mechanics. The second idea is Feynman's parton picture which he presented in 1969 at the Stony Brook conference on high-energy physics. The third idea is contained in the 1971 paper he published with his students, where they show that the hadronic spectra on Regge trajectories are manifestations of harmonic-oscillator degeneracies. In this report, we formulate these three ideas using the mathematics of two coupled oscillators. It is shown that the idea of entanglement is contained in his rest of the universe, and can be extended to a space-time entanglement. It is shown also that his parton model and the static quark model can be combined into one Lorentz-covariant entity. Furthermore, Einstein's special relativity, based on the Lorentz group, can also be formulated within the mathematical framework of two coupled oscillators.
NASA Astrophysics Data System (ADS)
Wang, Xiu-Xia
2016-02-01
By employing the generalized Hellmann-Feynman theorem, the quantization of mesoscopic complicated coupling circuit is proposed. The ensemble average energy, the energy fluctuation and the energy distribution are investigated at finite temperature. It is shown that the generalized Hellmann-Feynman theorem plays the key role in quantizing a mesoscopic complicated coupling circuit at finite temperature, and when the temperature is lower than the specific temperature, the value of (\\vartriangle {hat {H}})2 is almost zero and the values of
Generalizations of polylogarithms for Feynman integrals
NASA Astrophysics Data System (ADS)
Bogner, Christian
2016-10-01
In this talk, we discuss recent progress in the application of generalizations of polylogarithms in the symbolic computation of multi-loop integrals. We briefly review the Maple program MPL which supports a certain approach for the computation of Feynman integrals in terms of multiple polylogarithms. Furthermore we discuss elliptic generalizations of polylogarithms which have shown to be useful in the computation of the massive two-loop sunrise integral.
ERIC Educational Resources Information Center
Fanaro, Maria de los Angeles; Arlego, Marcelo; Otero, Maria Rita
2012-01-01
This work comprises an investigation about basic Quantum Mechanics (QM) teaching in the high school. The organization of the concepts does not follow a historical line. The Path Integrals method of Feynman has been adopted as a Reference Conceptual Structure that is an alternative to the canonical formalism. We have designed a didactic sequence…
Feynman-Kac equation for anomalous processes with space- and time-dependent forces
NASA Astrophysics Data System (ADS)
Cairoli, Andrea; Baule, Adrian
2017-04-01
Functionals of a stochastic process Y(t) model many physical time-extensive observables, for instance particle positions, local and occupation times or accumulated mechanical work. When Y(t) is a normal diffusive process, their statistics are obtained as the solution of the celebrated Feynman-Kac equation. This equation provides the crucial link between the expected values of diffusion processes and the solutions of deterministic second-order partial differential equations. When Y(t) is non-Brownian, e.g. an anomalous diffusive process, generalizations of the Feynman-Kac equation that incorporate power-law or more general waiting time distributions of the underlying random walk have recently been derived. A general representation of such waiting times is provided in terms of a Lévy process whose Laplace exponent is directly related to the memory kernel appearing in the generalized Feynman-Kac equation. The corresponding anomalous processes have been shown to capture nonlinear mean square displacements exhibiting crossovers between different scaling regimes, which have been observed in numerous experiments on biological systems like migrating cells or diffusing macromolecules in intracellular environments. However, the case where both space- and time-dependent forces drive the dynamics of the generalized anomalous process has not been solved yet. Here, we present the missing derivation of the Feynman-Kac equation in such general case by using the subordination technique. Furthermore, we discuss its extension to functionals explicitly depending on time, which are of particular relevance for the stochastic thermodynamics of anomalous diffusive systems. Exact results on the work fluctuations of a simple non-equilibrium model are obtained. An additional aim of this paper is to provide a pedagogical introduction to Lévy processes, semimartingales and their associated stochastic calculus, which underlie the mathematical formulation of anomalous diffusion as a subordinated process.
Supermanifolds from Feynman graphs
NASA Astrophysics Data System (ADS)
Marcolli, Matilde; Rej, Abhijnan
2008-08-01
We generalize the computation of Feynman integrals of log divergent graphs in terms of the Kirchhoff polynomial to the case of graphs with both fermionic and bosonic edges, to which we assign a set of ordinary and Grassmann variables. This procedure gives a computation of the Feynman integrals in terms of a period on a supermanifold, for graphs admitting a basis of the first homology satisfying a condition generalizing the log divergence in this context. The analog in this setting of the graph hypersurfaces is a graph supermanifold given by the divisor of zeros and poles of the Berezinian of a matrix associated with the graph, inside a superprojective space. We introduce a Grothendieck group for supermanifolds and identify the subgroup generated by the graph supermanifolds. This can be seen as a general procedure for constructing interesting classes of supermanifolds with associated periods.
New graph polynomials in parametric QED Feynman integrals
NASA Astrophysics Data System (ADS)
Golz, Marcel
2017-10-01
In recent years enormous progress has been made in perturbative quantum field theory by applying methods of algebraic geometry to parametric Feynman integrals for scalar theories. The transition to gauge theories is complicated not only by the fact that their parametric integrand is much larger and more involved. It is, moreover, only implicitly given as the result of certain differential operators applied to the scalar integrand exp(-ΦΓ /ΨΓ) , where ΨΓ and ΦΓ are the Kirchhoff and Symanzik polynomials of the Feynman graph Γ. In the case of quantum electrodynamics we find that the full parametric integrand inherits a rich combinatorial structure from ΨΓ and ΦΓ. In the end, it can be expressed explicitly as a sum over products of new types of graph polynomials which have a combinatoric interpretation via simple cycle subgraphs of Γ.
ERIC Educational Resources Information Center
Malgieri, Massimiliano; Tenni, Antonio; Onorato, Pasquale; De Ambrosis, Anna
2016-01-01
In this paper we present a reasoning line for introducing the Pauli exclusion principle in the context of an introductory course on quantum theory based on the sum over paths approach. We start from the argument originally introduced by Feynman in "QED: The Strange Theory of Light and Matter" and improve it by discussing with students…
Application of Generalized Feynman-Hellmann Theorem in Quantization of LC Circuit in Thermo Bath
NASA Astrophysics Data System (ADS)
Fan, Hong-Yi; Tang, Xu-Bing
For the quantized LC electric circuit, when taking the Joule thermal effect into account, we think that physical observables should be evaluated in the context of ensemble average. We then use the generalized Feynman-Hellmann theorem for ensemble average to calculate them, which seems convenient. Fluctuation of observables in various LC electric circuits in the presence of thermo bath growing with temperature is exhibited.
Geometry, Heat Equation and Path Integrals on the Poincaré Upper Half-Plane
NASA Astrophysics Data System (ADS)
Kubo, R.
1988-01-01
Geometry, heat equation and Feynman's path integrals are studied on the Poincaré upper half-plane. The fundamental solution to the heat equation partial f/partial t = Delta_{H} f is expressed in terms of a path integral defined on the upper half-plane. It is shown that Kac's statement that Feynman's path integral satisfies the Schrödinger equation is also valid for our case.
A test of the Feynman scaling in the fragmentation region
NASA Technical Reports Server (NTRS)
Doke, T.; Innocente, V.; Kasahara, K.; Kikuchi, J.; Kashiwagi, T.; Lanzano, S.; Masuda, K.; Murakami, H.; Muraki, Y.; Nakada, T.
1985-01-01
The result of the direct measurement of the fragmentation region will be presented. The result will be obtained at the CERN proton-antiproton collider, being exposured the Silicon calorimeters inside beam pipe. This experiment clarifies a long riddle of cosmic ray physics, whether the Feynman scaling does villate at the fragmentation region or the Iron component is increasing at 10 to the 15th power eV.
A Many-Body Formalism of ΔSCF Approach for Simulating X-Ray Spectra from First-Principles
NASA Astrophysics Data System (ADS)
Liang, Yufeng; Vinson, John; Pemmaraju, Sri; Drisdell, Walter; Shirley, Eric; Prendegast, David
Accurately reproducing X-ray spectral fingerprints for materials characterization relies heavily on how to correctly model the many-electron response to the generation of an X-ray core hole. In this talk, we present a novel first-principles theory for simulating X-ray spectra that is based on many-electron wavefunctions. The proposed theory go beyond the electron-hole correlations within the Bethe-Saltpeter Equation and consider higher-order vertex corrections up to the level of Mahan-Noziéres-De Dominicis (MND) theory. An efficient algorithm is invented to incorporate these many-electron processes by using linear algebra rather than iterating over all Feynman diag United States Department of Energy under Contact No. DE-AC02-05CH11231, No. DE-SC0004993.
A massive Feynman integral and some reduction relations for Appell functions
NASA Astrophysics Data System (ADS)
Shpot, M. A.
2007-12-01
New explicit expressions are derived for the one-loop two-point Feynman integral with arbitrary external momentum and masses m12 and m22 in D dimensions. The results are given in terms of Appell functions, manifestly symmetric with respect to the masses mi2. Equating our expressions with previously known results in terms of Gauss hypergeometric functions yields reduction relations for the involved Appell functions that are apparently new mathematical results.
New Tools for Forecasting Old Physics at the LHC
Dixon, Lance
2018-05-21
For the LHC to uncover many types of new physics, the "old physics" produced by the Standard Model must be understood very well. For decades, the central theoretical tool for this job was the Feynman diagram expansion. However, Feynman diagrams are just too slow, even on fast computers, to allow adequate precision for complicated LHC events with many jets in the final state. Such events are already visible in the initial LHC data. Over the past few years, alternative methods to Feynman diagrams have come to fruition. These new "on-shell" methods are based on the old principles of unitarity and factorization. They can be much more efficient because they exploit the underlying simplicity of scattering amplitudes, and recycle lower-loop information. I will describe how and why these methods work, and present some of the recent state-of-the-art results that have been obtained with them.
NASA Astrophysics Data System (ADS)
Radtke, T.; Fritzsche, S.
2008-11-01
Entanglement is known today as a key resource in many protocols from quantum computation and quantum information theory. However, despite the successful demonstration of several protocols, such as teleportation or quantum key distribution, there are still many open questions of how entanglement affects the efficiency of quantum algorithms or how it can be protected against noisy environments. The investigation of these and related questions often requires a search or optimization over the set of quantum states and, hence, a parametrization of them and various other objects. To facilitate this kind of studies in quantum information theory, here we present an extension of the FEYNMAN program that was developed during recent years as a toolbox for the simulation and analysis of quantum registers. In particular, we implement parameterizations of hermitian and unitary matrices (of arbitrary order), pure and mixed quantum states as well as separable states. In addition to being a prerequisite for the study of many optimization problems, these parameterizations also provide the necessary basis for heuristic studies which make use of random states, unitary matrices and other objects. Program summaryProgram title: FEYNMAN Catalogue identifier: ADWE_v4_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADWE_v4_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 24 231 No. of bytes in distributed program, including test data, etc.: 1 416 085 Distribution format: tar.gz Programming language: Maple 11 Computer: Any computer with Maple software installed Operating system: Any system that supports Maple; program has been tested under Microsoft Windows XP, Linux Classification: 4.15 Does the new version supersede the previous version?: Yes Nature of problem: During the last decades, quantum information science has contributed to our understanding of quantum mechanics and has provided also new and efficient protocols, based on the use of entangled quantum states. To determine the behavior and entanglement of n-qubit quantum registers, symbolic and numerical simulations need to be applied in order to analyze how these quantum information protocols work and which role the entanglement plays hereby. Solution method: Using the computer algebra system Maple, we have developed a set of procedures that support the definition, manipulation and analysis of n-qubit quantum registers. These procedures also help to deal with (unitary) logic gates and (nonunitary) quantum operations that act upon the quantum registers. With the parameterization of various frequently-applied objects, that are implemented in the present version, the program now facilitates a wider range of symbolic and numerical studies. All commands can be used interactively in order to simulate and analyze the evolution of n-qubit quantum systems, both in ideal and noisy quantum circuits. Reasons for new version: In the first version of the FEYNMAN program [1], we implemented the data structures and tools that are necessary to create, manipulate and to analyze the state of quantum registers. Later [2,3], support was added to deal with quantum operations (noisy channels) as an ingredient which is essential for studying the effects of decoherence. With the present extension, we add a number of parametrizations of objects frequently utilized in decoherence and entanglement studies, such that as hermitian and unitary matrices, probability distributions, or various kinds of quantum states. This extension therefore provides the basis, for example, for the optimization of a given function over the set of pure states or the simple generation of random objects. Running time: Most commands that act upon quantum registers with five or less qubits take ⩽10 seconds of processor time on a Pentium 4 processor with ⩾2GHz or newer, and about 5-20 MB of working memory (in addition to the memory for the Maple environment). Especially when working with symbolic expressions, however, the requirements on CPU time and memory critically depend on the size of the quantum registers, owing to the exponential growth of the dimension of the associated Hilbert space. For example, complex (symbolic) noise models, i.e. with several symbolic Kraus operators, result for multi-qubit systems often in very large expressions that dramatically slow down the evaluation of e.g. distance measures or the final-state entropy, etc. In these cases, Maple's assume facility sometimes helps to reduce the complexity of the symbolic expressions, but more often only a numerical evaluation is possible eventually. Since the complexity of the various commands of the FEYNMAN program and the possible usage scenarios can be very different, no general scaling law for CPU time or the memory requirements can be given. References: [1] T. Radtke, S. Fritzsche, Comput. Phys. Comm. 173 (2005) 91. [2] T. Radtke, S. Fritzsche, Comput. Phys. Comm. 175 (2006) 145. [3] T. Radtke, S. Fritzsche, Comput. Phys. Comm. 176 (2007) 617.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Croft, Stephen; Santi, Peter A.; Henzlova, Daniela
The Feynman-Y statistic is a type of autocorrelation analysis. It is defined as the excess variance-to-mean ratio, Y = VMR - 1, of the number count distribution formed by sampling a pulse train using a series of non-overlapping gates. It is a measure of the degree of correlation present on the pulse train with Y = 0 for Poisson data. In the context of neutron coincidence counting we show that the same information can be obtained from the accidentals histogram acquired using the multiplicity shift-register method, which is currently the common autocorrelation technique applied in nuclear safeguards. In the casemore » of multiplicity shift register analysis however, overlapping gates, either triggered by the incoming pulse stream or by a periodic clock, are used. The overlap introduces additional covariance but does not alter the expectation values. In this paper we discuss, for a particular data set, the relative merit of the Feynman and shift-register methods in terms of both precision and dead time correction. Traditionally the Feynman approach is applied with a relatively long gate width compared to the dieaway time. The main reason for this is so that the gate utilization factor can be taken as unity rather than being treated as a system parameter to be determined at characterization/calibration. But because the random trigger interval gate utilization factor is slow to saturate this procedure requires a gate width many times the effective 1/e dieaway time. In the traditional approach this limits the number of gates that can be fitted into a given assay duration. We empirically show that much shorter gates, similar in width to those used in traditional shift register analysis can be used. Because the way in which the correlated information present on the pulse train is extracted is different for the moments based method of Feynman and the various shift register based approaches, the dead time losses are manifested differently for these two approaches. The resulting estimates for the dead time corrected first and second order reduced factorial moments should be independent of the method however and this allows the respective dead time formalism to be checked. We discuss how to make dead time corrections in both the shift register and the Feynman approaches.« less
NASA Astrophysics Data System (ADS)
Fan, Hong-Yi; Xu, Xue-Xiang; Hu, Li-Yun
2010-06-01
By virtue of the generalized Hellmann-Feynman theorem for the ensemble average, we obtain the internal energy and average energy consumed by the resistance R in a quantized resistance-inductance-capacitance (RLC) electric circuit. We also calculate the entropy-variation with R. The relation between entropy and R is also derived. By the use of figures we indeed see that the entropy increases with the increment of R.
Destructive interferences results in bosons anti bunching: refining Feynman's argument
NASA Astrophysics Data System (ADS)
Marchewka, Avi; Granot, Er'el
2014-09-01
The effect of boson bunching is frequently mentioned and discussed in the literature. This effect is the manifestation of bosons tendency to "travel" in clusters. One of the core arguments for boson bunching was formulated by Feynman in his well-known lecture series and has been frequently used ever since. By comparing the scattering probabilities of two bosons and of two distinguishable particles, he concluded: "We have the result that it is twice as likely to find two identical Bose particles scattered into the same state as you would calculate assuming the particles were different" [R.P. Feynman, R.B. Leighton, M. Sands, The Feynman Lectures on Physics: Quantum mechanics (Addison-Wesley, 1965)]. This argument was rooted in the scientific community (see for example [C. Cohen-Tannoudji, B. Diu, F. Laloë, Quantum Mechanics (John Wiley & Sons, Paris, 1977); W. Pauli, Exclusion Principle and Quantum Mechanics, Nobel Lecture (1946)]), however, while this sentence is completely valid, as is proved in [C. Cohen-Tannoudji, B. Diu, F. Laloë, Quantum Mechanics (John Wiley & Sons, Paris, 1977)], it is not a synonym of bunching. In fact, as it is shown in this paper, wherever one of the wavefunctions has a zero, bosons can anti-bunch and fermions can bunch. It should be stressed that zeros in the wavefunctions are ubiquitous in Quantum Mechanics and therefore the effect should be common. Several scenarios are suggested to witness the effect.
JaxoDraw: A graphical user interface for drawing Feynman diagrams
NASA Astrophysics Data System (ADS)
Binosi, D.; Theußl, L.
2004-08-01
JaxoDraw is a Feynman graph plotting tool written in Java. It has a complete graphical user interface that allows all actions to be carried out via mouse click-and-drag operations in a WYSIWYG fashion. Graphs may be exported to postscript/EPS format and can be saved in XML files to be used for later sessions. One of JaxoDraw's main features is the possibility to create ? code that may be used to generate graphics output, thus combining the powers of ? with those of a modern day drawing program. With JaxoDraw it becomes possible to draw even complicated Feynman diagrams with just a few mouse clicks, without the knowledge of any programming language. Program summaryTitle of program: JaxoDraw Catalogue identifier: ADUA Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADUA Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Distribution format: tar gzip file Operating system: Any Java-enabled platform, tested on Linux, Windows ME, XP, Mac OS X Programming language used: Java License: GPL Nature of problem: Existing methods for drawing Feynman diagrams usually require some 'hard-coding' in one or the other programming or scripting language. It is not very convenient and often time consuming, to generate relatively simple diagrams. Method of solution: A program is provided that allows for the interactive drawing of Feynman diagrams with a graphical user interface. The program is easy to learn and use, produces high quality output in several formats and runs on any operating system where a Java Runtime Environment is available. Number of bytes in distributed program, including test data: 2 117 863 Number of lines in distributed program, including test data: 60 000 Restrictions: Certain operations (like internal latex compilation, Postscript preview) require the execution of external commands that might not work on untested operating systems. Typical running time: As an interactive program, the running time depends on the complexity of the diagram to be drawn.
Atomic Manipulation on Metal Surfaces
NASA Astrophysics Data System (ADS)
Ternes, Markus; Lutz, Christopher P.; Heinrich, Andreas J.
Half a century ago, Nobel Laureate Richard Feynman asked in a now-famous lecture what would happen if we could precisely position individual atoms at will [R.P. Feynman, Eng. Sci. 23, 22 (1960)]. This dream became a reality some 30 years later when Eigler and Schweizer were the first to position individual Xe atoms at will with the probe tip of a low-temperature scanning tunneling microscope (STM) on a Ni surface [D.M. Eigler, E.K. Schweizer, Nature 344, 524 (1990)].
Self-consistent continuum solvation for optical absorption of complex molecular systems in solution
DOE Office of Scientific and Technical Information (OSTI.GOV)
Timrov, Iurii; Biancardi, Alessandro; Andreussi, Oliviero
2015-01-21
We introduce a new method to compute the optical absorption spectra of complex molecular systems in solution, based on the Liouville approach to time-dependent density-functional perturbation theory and the revised self-consistent continuum solvation model. The former allows one to obtain the absorption spectrum over a whole wide frequency range, using a recently proposed Lanczos-based technique, or selected excitation energies, using the Casida equation, without having to ever compute any unoccupied molecular orbitals. The latter is conceptually similar to the polarizable continuum model and offers the further advantages of allowing an easy computation of atomic forces via the Hellmann-Feynman theorem andmore » a ready implementation in periodic-boundary conditions. The new method has been implemented using pseudopotentials and plane-wave basis sets, benchmarked against polarizable continuum model calculations on 4-aminophthalimide, alizarin, and cyanin and made available through the QUANTUM ESPRESSO distribution of open-source codes.« less
Evaluating Feynman integrals by the hypergeometry
NASA Astrophysics Data System (ADS)
Feng, Tai-Fu; Chang, Chao-Hsi; Chen, Jian-Bin; Gu, Zhi-Hua; Zhang, Hai-Bin
2018-02-01
The hypergeometric function method naturally provides the analytic expressions of scalar integrals from concerned Feynman diagrams in some connected regions of independent kinematic variables, also presents the systems of homogeneous linear partial differential equations satisfied by the corresponding scalar integrals. Taking examples of the one-loop B0 and massless C0 functions, as well as the scalar integrals of two-loop vacuum and sunset diagrams, we verify our expressions coinciding with the well-known results of literatures. Based on the multiple hypergeometric functions of independent kinematic variables, the systems of homogeneous linear partial differential equations satisfied by the mentioned scalar integrals are established. Using the calculus of variations, one recognizes the system of linear partial differential equations as stationary conditions of a functional under some given restrictions, which is the cornerstone to perform the continuation of the scalar integrals to whole kinematic domains numerically with the finite element methods. In principle this method can be used to evaluate the scalar integrals of any Feynman diagrams.
An update on the BQCD Hybrid Monte Carlo program
NASA Astrophysics Data System (ADS)
Haar, Taylor Ryan; Nakamura, Yoshifumi; Stüben, Hinnerk
2018-03-01
We present an update of BQCD, our Hybrid Monte Carlo program for simulating lattice QCD. BQCD is one of the main production codes of the QCDSF collaboration and is used by CSSM and in some Japanese finite temperature and finite density projects. Since the first publication of the code at Lattice 2010 the program has been extended in various ways. New features of the code include: dynamical QED, action modification in order to compute matrix elements by using Feynman-Hellman theory, more trace measurements (like Tr(D-n) for K, cSW and chemical potential reweighting), a more flexible integration scheme, polynomial filtering, term-splitting for RHMC, and a portable implementation of performance critical parts employing SIMD.
Simulation of n-qubit quantum systems. III. Quantum operations
NASA Astrophysics Data System (ADS)
Radtke, T.; Fritzsche, S.
2007-05-01
During the last decade, several quantum information protocols, such as quantum key distribution, teleportation or quantum computation, have attracted a lot of interest. Despite the recent success and research efforts in quantum information processing, however, we are just at the beginning of understanding the role of entanglement and the behavior of quantum systems in noisy environments, i.e. for nonideal implementations. Therefore, in order to facilitate the investigation of entanglement and decoherence in n-qubit quantum registers, here we present a revised version of the FEYNMAN program for working with quantum operations and their associated (Jamiołkowski) dual states. Based on the implementation of several popular decoherence models, we provide tools especially for the quantitative analysis of quantum operations. Apart from the implementation of different noise models, the current program extension may help investigate the fragility of many quantum states, one of the main obstacles in realizing quantum information protocols today. Program summaryTitle of program: Feynman Catalogue identifier: ADWE_v3_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADWE_v3_0 Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Licensing provisions: None Operating systems: Any system that supports MAPLE; tested under Microsoft Windows XP, SuSe Linux 10 Program language used:MAPLE 10 Typical time and memory requirements: Most commands that act upon quantum registers with five or less qubits take ⩽10 seconds of processor time (on a Pentium 4 processor with ⩾2 GHz or equivalent) and 5-20 MB of memory. Especially when working with symbolic expressions, however, the memory and time requirements critically depend on the number of qubits in the quantum registers, owing to the exponential dimension growth of the associated Hilbert space. For example, complex (symbolic) noise models (with several Kraus operators) for multi-qubit systems often result in very large symbolic expressions that dramatically slow down the evaluation of measures or other quantities. In these cases, MAPLE's assume facility sometimes helps to reduce the complexity of symbolic expressions, but often only numerical evaluation is possible. Since the complexity of the FEYNMAN commands is very different, no general scaling law for the CPU time and memory usage can be given. No. of bytes in distributed program including test data, etc.: 799 265 No. of lines in distributed program including test data, etc.: 18 589 Distribution format: tar.gz Reasons for new version: While the previous program versions were designed mainly to create and manipulate the state of quantum registers, the present extension aims to support quantum operations as the essential ingredient for studying the effects of noisy environments. Does this version supersede the previous version: Yes Nature of the physical problem: Today, entanglement is identified as the essential resource in virtually all aspects of quantum information theory. In most practical implementations of quantum information protocols, however, decoherence typically limits the lifetime of entanglement. It is therefore necessary and highly desirable to understand the evolution of entanglement in noisy environments. Method of solution: Using the computer algebra system MAPLE, we have developed a set of procedures that support the definition and manipulation of n-qubit quantum registers as well as (unitary) logic gates and (nonunitary) quantum operations that act on the quantum registers. The provided hierarchy of commands can be used interactively in order to simulate and analyze the evolution of n-qubit quantum systems in ideal and nonideal quantum circuits.
Renormalized asymptotic enumeration of Feynman diagrams
NASA Astrophysics Data System (ADS)
Borinsky, Michael
2017-10-01
A method to obtain all-order asymptotic results for the coefficients of perturbative expansions in zero-dimensional quantum field is described. The focus is on the enumeration of the number of skeleton or primitive diagrams of a certain QFT and its asymptotics. The procedure heavily applies techniques from singularity analysis. To utilize singularity analysis, a representation of the zero-dimensional path integral as a generalized hyperelliptic curve is deduced. As applications the full asymptotic expansions of the number of disconnected, connected, 1PI and skeleton Feynman diagrams in various theories are given.
Feynman’s clock, a new variational principle, and parallel-in-time quantum dynamics
McClean, Jarrod R.; Parkhill, John A.; Aspuru-Guzik, Alán
2013-01-01
We introduce a discrete-time variational principle inspired by the quantum clock originally proposed by Feynman and use it to write down quantum evolution as a ground-state eigenvalue problem. The construction allows one to apply ground-state quantum many-body theory to quantum dynamics, extending the reach of many highly developed tools from this fertile research area. Moreover, this formalism naturally leads to an algorithm to parallelize quantum simulation over time. We draw an explicit connection between previously known time-dependent variational principles and the time-embedded variational principle presented. Sample calculations are presented, applying the idea to a hydrogen molecule and the spin degrees of freedom of a model inorganic compound, demonstrating the parallel speedup of our method as well as its flexibility in applying ground-state methodologies. Finally, we take advantage of the unique perspective of this variational principle to examine the error of basis approximations in quantum dynamics. PMID:24062428
Dynamics of a Two-Dimensional System of Quantum Dipoles
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mazzanti, F.; Astrakharchik, G. E.; Boronat, J.
2009-03-20
A detailed microscopic analysis of the dynamic structure function S(k,{omega}) of a two-dimensional Bose system of dipoles polarized along the direction perpendicular to the plane is presented and discussed. Starting from ground-state quantities obtained using a quantum diffusion Monte Carlo algorithm, the density-density response is evaluated in the context of the correlated basis functions (CBF) theory. CBF predicts a sharp peak and a multiexcitation component at higher energies produced by the decay of excitations. We discuss the structure of the phonon-roton peak and show that the Feynman and Bogoliubov predictions depart from the CBF result already at low densities. Wemore » finally discuss the emergence of a roton in the spectrum, but find the roton energy not low enough to make the system unstable under density fluctuations up to the highest density considered that is close to the freezing point.« less
VLSI Implementation of Fault Tolerance Multiplier based on Reversible Logic Gate
NASA Astrophysics Data System (ADS)
Ahmad, Nabihah; Hakimi Mokhtar, Ahmad; Othman, Nurmiza binti; Fhong Soon, Chin; Rahman, Ab Al Hadi Ab
2017-08-01
Multiplier is one of the essential component in the digital world such as in digital signal processing, microprocessor, quantum computing and widely used in arithmetic unit. Due to the complexity of the multiplier, tendency of errors are very high. This paper aimed to design a 2×2 bit Fault Tolerance Multiplier based on Reversible logic gate with low power consumption and high performance. This design have been implemented using 90nm Complemetary Metal Oxide Semiconductor (CMOS) technology in Synopsys Electronic Design Automation (EDA) Tools. Implementation of the multiplier architecture is by using the reversible logic gates. The fault tolerance multiplier used the combination of three reversible logic gate which are Double Feynman gate (F2G), New Fault Tolerance (NFT) gate and Islam Gate (IG) with the area of 160μm x 420.3μm (67.25 mm2). This design achieved a low power consumption of 122.85μW and propagation delay of 16.99ns. The fault tolerance multiplier proposed achieved a low power consumption and high performance which suitable for application of modern computing as it has a fault tolerance capabilities.
A real time microcomputer implementation of sensor failure detection for turbofan engines
NASA Technical Reports Server (NTRS)
Delaat, John C.; Merrill, Walter C.
1989-01-01
An algorithm was developed which detects, isolates, and accommodates sensor failures using analytical redundancy. The performance of this algorithm was demonstrated on a full-scale F100 turbofan engine. The algorithm was implemented in real-time on a microprocessor-based controls computer which includes parallel processing and high order language programming. Parallel processing was used to achieve the required computational power for the real-time implementation. High order language programming was used in order to reduce the programming and maintenance costs of the algorithm implementation software. The sensor failure algorithm was combined with an existing multivariable control algorithm to give a complete control implementation with sensor analytical redundancy. The real-time microprocessor implementation of the algorithm which resulted in the successful completion of the algorithm engine demonstration, is described.
Advances in the computation of the Sjöstrand, Rossi, and Feynman distributions
Talamo, A.; Gohar, Y.; Gabrielli, F.; ...
2017-02-01
This study illustrates recent computational advances in the application of the Sjöstrand (area), Rossi, and Feynman methods to estimate the effective multiplication factor of a subcritical system driven by an external neutron source. The methodologies introduced in this study have been validated with the experimental results from the KUKA facility of Japan by Monte Carlo (MCNP6 and MCNPX) and deterministic (ERANOS, VARIANT, and PARTISN) codes. When the assembly is driven by a pulsed neutron source generated by a particle accelerator and delayed neutrons are at equilibrium, the Sjöstrand method becomes extremely fast if the integral of the reaction rate frommore » a single pulse is split into two parts. These two integrals distinguish between the neutron counts during and after the pulse period. To conclude, when the facility is driven by a spontaneous fission neutron source, the timestamps of the detector neutron counts can be obtained up to the nanosecond precision using MCNP6, which allows obtaining the Rossi and Feynman distributions.« less
Infinities in Quantum Field Theory and in Classical Computing: Renormalization Program
NASA Astrophysics Data System (ADS)
Manin, Yuri I.
Introduction. The main observable quantities in Quantum Field Theory, correlation functions, are expressed by the celebrated Feynman path integrals. A mathematical definition of them involving a measure and actual integration is still lacking. Instead, it is replaced by a series of ad hoc but highly efficient and suggestive heuristic formulas such as perturbation formalism. The latter interprets such an integral as a formal series of finite-dimensional but divergent integrals, indexed by Feynman graphs, the list of which is determined by the Lagrangian of the theory. Renormalization is a prescription that allows one to systematically "subtract infinities" from these divergent terms producing an asymptotic series for quantum correlation functions. On the other hand, graphs treated as "flowcharts", also form a combinatorial skeleton of the abstract computation theory. Partial recursive functions that according to Church's thesis exhaust the universe of (semi)computable maps are generally not everywhere defined due to potentially infinite searches and loops. In this paper I argue that such infinities can be addressed in the same way as Feynman divergences. More details can be found in [9,10].
Global Estimates of Errors in Quantum Computation by the Feynman-Vernon Formalism
NASA Astrophysics Data System (ADS)
Aurell, Erik
2018-06-01
The operation of a quantum computer is considered as a general quantum operation on a mixed state on many qubits followed by a measurement. The general quantum operation is further represented as a Feynman-Vernon double path integral over the histories of the qubits and of an environment, and afterward tracing out the environment. The qubit histories are taken to be paths on the two-sphere S^2 as in Klauder's coherent-state path integral of spin, and the environment is assumed to consist of harmonic oscillators initially in thermal equilibrium, and linearly coupled to to qubit operators \\hat{S}_z. The environment can then be integrated out to give a Feynman-Vernon influence action coupling the forward and backward histories of the qubits. This representation allows to derive in a simple way estimates that the total error of operation of a quantum computer without error correction scales linearly with the number of qubits and the time of operation. It also allows to discuss Kitaev's toric code interacting with an environment in the same manner.
Global Estimates of Errors in Quantum Computation by the Feynman-Vernon Formalism
NASA Astrophysics Data System (ADS)
Aurell, Erik
2018-04-01
The operation of a quantum computer is considered as a general quantum operation on a mixed state on many qubits followed by a measurement. The general quantum operation is further represented as a Feynman-Vernon double path integral over the histories of the qubits and of an environment, and afterward tracing out the environment. The qubit histories are taken to be paths on the two-sphere S^2 as in Klauder's coherent-state path integral of spin, and the environment is assumed to consist of harmonic oscillators initially in thermal equilibrium, and linearly coupled to to qubit operators \\hat{S}_z . The environment can then be integrated out to give a Feynman-Vernon influence action coupling the forward and backward histories of the qubits. This representation allows to derive in a simple way estimates that the total error of operation of a quantum computer without error correction scales linearly with the number of qubits and the time of operation. It also allows to discuss Kitaev's toric code interacting with an environment in the same manner.
Squeezed states, time-energy uncertainty relation, and Feynman's rest of the universe
NASA Technical Reports Server (NTRS)
Han, D.; Kim, Y. S.; Noz, Marilyn E.
1992-01-01
Two illustrative examples are given for Feynman's rest of the universe. The first example is the two-mode squeezed state of light where no measurement is taken for one of the modes. The second example is the relativistic quark model where no measurement is possible for the time-like separation fo quarks confined in a hadron. It is possible to illustrate these examples using the covariant oscillator formalism. It is shown that the lack of symmetry between the position-momentum and time-energy uncertainty relations leads to an increase in entropy when the system is different Lorentz frames.
On critical exponents without Feynman diagrams
NASA Astrophysics Data System (ADS)
Sen, Kallol; Sinha, Aninda
2016-11-01
In order to achieve a better analytic handle on the modern conformal bootstrap program, we re-examine and extend the pioneering 1974 work of Polyakov’s, which was based on consistency between the operator product expansion and unitarity. As in the bootstrap approach, this method does not depend on evaluating Feynman diagrams. We show how this approach can be used to compute the anomalous dimensions of certain operators in the O(n) model at the Wilson-Fisher fixed point in 4-ɛ dimensions up to O({ɛ }2). AS dedicates this work to the loving memory of his mother.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Juffmann, Thomas; Koppell, Stewart A.; Klopfer, Brannon B.
Feynman once asked physicists to build better electron microscopes to be able to watch biology at work. While electron microscopes can now provide atomic resolution, electron beam induced specimen damage precludes high resolution imaging of sensitive materials, such as single proteins or polymers. Here, we use simulations to show that an electron microscope based on a multi-pass measurement protocol enables imaging of single proteins, without averaging structures over multiple images. While we demonstrate the method for particular imaging targets, the approach is broadly applicable and is expected to improve resolution and sensitivity for a range of electron microscopy imaging modalities,more » including, for example, scanning and spectroscopic techniques. The approach implements a quantum mechanically optimal strategy which under idealized conditions can be considered interaction-free.« less
Perturbation theory in light-cone quantization
DOE Office of Scientific and Technical Information (OSTI.GOV)
Langnau, A.
1992-01-01
A thorough investigation of light-cone properties which are characteristic for higher dimensions is very important. The easiest way of addressing these issues is by analyzing the perturbative structure of light-cone field theories first. Perturbative studies cannot be substituted for an analysis of problems related to a nonperturbative approach. However, in order to lay down groundwork for upcoming nonperturbative studies, it is indispensable to validate the renormalization methods at the perturbative level, i.e., to gain control over the perturbative treatment first. A clear understanding of divergences in perturbation theory, as well as their numerical treatment, is a necessary first step towardsmore » formulating such a program. The first objective of this dissertation is to clarify this issue, at least in second and fourth-order in perturbation theory. The work in this dissertation can provide guidance for the choice of counterterms in Discrete Light-Cone Quantization or the Tamm-Dancoff approach. A second objective of this work is the study of light-cone perturbation theory as a competitive tool for conducting perturbative Feynman diagram calculations. Feynman perturbation theory has become the most practical tool for computing cross sections in high energy physics and other physical properties of field theory. Although this standard covariant method has been applied to a great range of problems, computations beyond one-loop corrections are very difficult. Because of the algebraic complexity of the Feynman calculations in higher-order perturbation theory, it is desirable to automatize Feynman diagram calculations so that algebraic manipulation programs can carry out almost the entire calculation. This thesis presents a step in this direction. The technique we are elaborating on here is known as light-cone perturbation theory.« less
Algorithms Bridging Quantum Computation and Chemistry
NASA Astrophysics Data System (ADS)
McClean, Jarrod Ryan
The design of new materials and chemicals derived entirely from computation has long been a goal of computational chemistry, and the governing equation whose solution would permit this dream is known. Unfortunately, the exact solution to this equation has been far too expensive and clever approximations fail in critical situations. Quantum computers offer a novel solution to this problem. In this work, we develop not only new algorithms to use quantum computers to study hard problems in chemistry, but also explore how such algorithms can help us to better understand and improve our traditional approaches. In particular, we first introduce a new method, the variational quantum eigensolver, which is designed to maximally utilize the quantum resources available in a device to solve chemical problems. We apply this method in a real quantum photonic device in the lab to study the dissociation of the helium hydride (HeH+) molecule. We also enhance this methodology with architecture specific optimizations on ion trap computers and show how linear-scaling techniques from traditional quantum chemistry can be used to improve the outlook of similar algorithms on quantum computers. We then show how studying quantum algorithms such as these can be used to understand and enhance the development of classical algorithms. In particular we use a tool from adiabatic quantum computation, Feynman's Clock, to develop a new discrete time variational principle and further establish a connection between real-time quantum dynamics and ground state eigenvalue problems. We use these tools to develop two novel parallel-in-time quantum algorithms that outperform competitive algorithms as well as offer new insights into the connection between the fermion sign problem of ground states and the dynamical sign problem of quantum dynamics. Finally we use insights gained in the study of quantum circuits to explore a general notion of sparsity in many-body quantum systems. In particular we use developments from the field of compressed sensing to find compact representations of ground states. As an application we study electronic systems and find solutions dramatically more compact than traditional configuration interaction expansions, offering hope to extend this methodology to challenging systems in chemical and material design.
NASA Astrophysics Data System (ADS)
Zhang, Guannan; Del-Castillo-Negrete, Diego
2017-10-01
Kinetic descriptions of RE are usually based on the bounced-averaged Fokker-Planck model that determines the PDFs of RE. Despite of the simplification involved, the Fokker-Planck equation can rarely be solved analytically and direct numerical approaches (e.g., continuum and particle-based Monte Carlo (MC)) can be time consuming specially in the computation of asymptotic-type observable including the runaway probability, the slowing-down and runaway mean times, and the energy limit probability. Here we present a novel backward MC approach to these problems based on backward stochastic differential equations (BSDEs). The BSDE model can simultaneously describe the PDF of RE and the runaway probabilities by means of the well-known Feynman-Kac theory. The key ingredient of the backward MC algorithm is to place all the particles in a runaway state and simulate them backward from the terminal time to the initial time. As such, our approach can provide much faster convergence than the brute-force MC methods, which can significantly reduce the number of particles required to achieve a prescribed accuracy. Moreover, our algorithm can be parallelized as easy as the direct MC code, which paves the way for conducting large-scale RE simulation. This work is supported by DOE FES and ASCR under the Contract Numbers ERKJ320 and ERAT377.
Bold Diagrammatic Monte Carlo for Fermionic and Fermionized Systems
NASA Astrophysics Data System (ADS)
Svistunov, Boris
2013-03-01
In three different fermionic cases--repulsive Hubbard model, resonant fermions, and fermionized spins-1/2 (on triangular lattice)--we observe the phenomenon of sign blessing: Feynman diagrammatic series features finite convergence radius despite factorial growth of the number of diagrams with diagram order. Bold diagrammatic Monte Carlo technique allows us to sample millions of skeleton Feynman diagrams. With the universal fermionization trick we can fermionize essentially any (bosonic, spin, mixed, etc.) lattice system. The combination of fermionization and Bold diagrammatic Monte Carlo yields a universal first-principle approach to strongly correlated lattice systems, provided the sign blessing is a generic fermionic phenomenon. Supported by NSF and DARPA
Poisson equation for the Mercedes diagram in string theory at genus one
NASA Astrophysics Data System (ADS)
Basu, Anirban
2016-03-01
The Mercedes diagram has four trivalent vertices which are connected by six links such that they form the edges of a tetrahedron. This three-loop Feynman diagram contributes to the {D}12{{ R }}4 amplitude at genus one in type II string theory, where the vertices are the points of insertion of the graviton vertex operators, and the links are the scalar propagators on the toroidal worldsheet. We obtain a modular invariant Poisson equation satisfied by the Mercedes diagram, where the source terms involve one- and two-loop Feynman diagrams. We calculate its contribution to the {D}12{{ R }}4 amplitude.
Electron propagator calculations on the ionization energies of CrH -, MnH - and FeH -
NASA Astrophysics Data System (ADS)
Lin, Jyh-Shing; Ortiz, J. V.
1990-08-01
Electron propagator calculations with unrestricted Hartree-Fock reference states yield the ionization energies of the title anions. Spin contamination in the anionic reference state is small, enabling the use of second-and third-order self-energies in the Dyson equation. Feynman-Dyson amplitudes for these ionizations are essentially identical to canonical spin-orbitals. For most of the final states, these consist of an antibonding combination of an sp metal hybrid, polarized away from the hydrogen, and hydroegen s functions. In one case, the Feynman-Dyson amplitude consists of nonbonding d functions. Calculated ionization energies are within 0.5 eV of experiment.
Gravity, Time, and Lagrangians
NASA Astrophysics Data System (ADS)
Huggins, Elisha
2010-11-01
Feynman mentioned to us that he understood a topic in physics if he could explain it to a college freshman, a high school student, or a dinner guest. Here we will discuss two topics that took us a while to get to that level. One is the relationship between gravity and time. The other is the minus sign that appears in the Lagrangian. (Why would one subtract potential energy from kinetic energy?) In this paper we discuss a thought experiment that relates gravity and time. Then we use a Feynman thought experiment to explain the minus sign in the Lagrangian. Our surprise was that these two topics are related.
Extended Hellmann-Feynman theorem for degenerate eigenstates
NASA Astrophysics Data System (ADS)
Zhang, G. P.; George, Thomas F.
2004-04-01
In a previous paper, we reported a failure of the traditional Hellmann-Feynman theorem (HFT) for degenerate eigenstates. This has generated enormous interest among different groups. In four independent papers by Fernandez, by Balawender, Hola, and March, by Vatsya, and by Alon and Cederbaum, an elegant method to solve the problem was devised. The main idea is that one has to construct and diagonalize the force matrix for the degenerate case, and only the eigenforces are well defined. We believe this is an important extension to HFT. Using our previous example for an energy level of fivefold degeneracy, we find that those eigenforces correctly reflect the symmetry of the molecule.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Altmeyer, Michaela; Guterding, Daniel; Hirschfeld, P. J.
2016-12-21
In the framework of a multiorbital Hubbard model description of superconductivity, a matrix formulation of the superconducting pairing interaction that has been widely used is designed to treat spin, charge, and orbital fluctuations within a random phase approximation (RPA). In terms of Feynman diagrams, this takes into account particle-hole ladder and bubble contributions as expected. It turns out, however, that this matrix formulation also generates additional terms which have the diagrammatic structure of vertex corrections. Furthermore we examine these terms and discuss the relationship between the matrix-RPA superconducting pairing interaction and the Feynman diagrams that it sums.
Feynman rules for the Standard Model Effective Field Theory in R ξ -gauges
NASA Astrophysics Data System (ADS)
Dedes, A.; Materkowska, W.; Paraskevas, M.; Rosiek, J.; Suxho, K.
2017-06-01
We assume that New Physics effects are parametrized within the Standard Model Effective Field Theory (SMEFT) written in a complete basis of gauge invariant operators up to dimension 6, commonly referred to as "Warsaw basis". We discuss all steps necessary to obtain a consistent transition to the spontaneously broken theory and several other important aspects, including the BRST-invariance of the SMEFT action for linear R ξ -gauges. The final theory is expressed in a basis characterized by SM-like propagators for all physical and unphysical fields. The effect of the non-renormalizable operators appears explicitly in triple or higher multiplicity vertices. In this mass basis we derive the complete set of Feynman rules, without resorting to any simplifying assumptions such as baryon-, lepton-number or CP conservation. As it turns out, for most SMEFT vertices the expressions are reasonably short, with a noticeable exception of those involving 4, 5 and 6 gluons. We have also supplemented our set of Feynman rules, given in an appendix here, with a publicly available Mathematica code working with the FeynRules package and producing output which can be integrated with other symbolic algebra or numerical codes for automatic SMEFT amplitude calculations.
Efficient Scalable Median Filtering Using Histogram-Based Operations.
Green, Oded
2018-05-01
Median filtering is a smoothing technique for noise removal in images. While there are various implementations of median filtering for a single-core CPU, there are few implementations for accelerators and multi-core systems. Many parallel implementations of median filtering use a sorting algorithm for rearranging the values within a filtering window and taking the median of the sorted value. While using sorting algorithms allows for simple parallel implementations, the cost of the sorting becomes prohibitive as the filtering windows grow. This makes such algorithms, sequential and parallel alike, inefficient. In this work, we introduce the first software parallel median filtering that is non-sorting-based. The new algorithm uses efficient histogram-based operations. These reduce the computational requirements of the new algorithm while also accessing the image fewer times. We show an implementation of our algorithm for both the CPU and NVIDIA's CUDA supported graphics processing unit (GPU). The new algorithm is compared with several other leading CPU and GPU implementations. The CPU implementation has near perfect linear scaling with a speedup on a quad-core system. The GPU implementation is several orders of magnitude faster than the other GPU implementations for mid-size median filters. For small kernels, and , comparison-based approaches are preferable as fewer operations are required. Lastly, the new algorithm is open-source and can be found in the OpenCV library.
An Object-Oriented Collection of Minimum Degree Algorithms: Design, Implementation, and Experiences
NASA Technical Reports Server (NTRS)
Kumfert, Gary; Pothen, Alex
1999-01-01
The multiple minimum degree (MMD) algorithm and its variants have enjoyed 20+ years of research and progress in generating fill-reducing orderings for sparse, symmetric positive definite matrices. Although conceptually simple, efficient implementations of these algorithms are deceptively complex and highly specialized. In this case study, we present an object-oriented library that implements several recent minimum degree-like algorithms. We discuss how object-oriented design forces us to decompose these algorithms in a different manner than earlier codes and demonstrate how this impacts the flexibility and efficiency of our C++ implementation. We compare the performance of our code against other implementations in C or Fortran.
Multi-pass transmission electron microscopy
Juffmann, Thomas; Koppell, Stewart A.; Klopfer, Brannon B.; ...
2017-05-10
Feynman once asked physicists to build better electron microscopes to be able to watch biology at work. While electron microscopes can now provide atomic resolution, electron beam induced specimen damage precludes high resolution imaging of sensitive materials, such as single proteins or polymers. Here, we use simulations to show that an electron microscope based on a multi-pass measurement protocol enables imaging of single proteins, without averaging structures over multiple images. While we demonstrate the method for particular imaging targets, the approach is broadly applicable and is expected to improve resolution and sensitivity for a range of electron microscopy imaging modalities,more » including, for example, scanning and spectroscopic techniques. The approach implements a quantum mechanically optimal strategy which under idealized conditions can be considered interaction-free.« less
Data Compression for Maskless Lithography Systems: Architecture, Algorithms and Implementation
2008-05-19
Data Compression for Maskless Lithography Systems: Architecture, Algorithms and Implementation Vito Dai Electrical Engineering and Computer Sciences...servers or to redistribute to lists, requires prior specific permission. Data Compression for Maskless Lithography Systems: Architecture, Algorithms and...for Maskless Lithography Systems: Architecture, Algorithms and Implementation Copyright 2008 by Vito Dai 1 Abstract Data Compression for Maskless
Neutrino oscillation processes in a quantum-field-theoretical approach
NASA Astrophysics Data System (ADS)
Egorov, Vadim O.; Volobuev, Igor P.
2018-05-01
It is shown that neutrino oscillation processes can be consistently described in the framework of quantum field theory using only the plane wave states of the particles. Namely, the oscillating electron survival probabilities in experiments with neutrino detection by charged-current and neutral-current interactions are calculated in the quantum field-theoretical approach to neutrino oscillations based on a modification of the Feynman propagator in the momentum representation. The approach is most similar to the standard Feynman diagram technique. It is found that the oscillating distance-dependent probabilities of detecting an electron in experiments with neutrino detection by charged-current and neutral-current interactions exactly coincide with the corresponding probabilities calculated in the standard approach.
NASA Technical Reports Server (NTRS)
Straton, Jack C.
1989-01-01
The Fourier transform of the multicenter product of N 1s hydrogenic orbitals and M Coulomb or Yukawa potentials is given as an (M+N-1)-dimensional Feynman integral with external momenta and shifted coordinates. This is accomplished through the introduction of an integral transformation, in addition to the standard Feynman transformation for the denominators of the momentum representation of the terms in the product, which moves the resulting denominator into an exponential. This allows the angular dependence of the denominator to be combined with the angular dependence in the plane waves.
Bosonic Loop Diagrams as Perturbative Solutions of the Classical Field Equations in ϕ4-Theory
NASA Astrophysics Data System (ADS)
Finster, Felix; Tolksdorf, Jürgen
2012-05-01
Solutions of the classical ϕ4-theory in Minkowski space-time are analyzed in a perturbation expansion in the nonlinearity. Using the language of Feynman diagrams, the solution of the Cauchy problem is expressed in terms of tree diagrams which involve the retarded Green's function and have one outgoing leg. In order to obtain general tree diagrams, we set up a "classical measurement process" in which a virtual observer of a scattering experiment modifies the field and detects suitable energy differences. By adding a classical stochastic background field, we even obtain all loop diagrams. The expansions are compared with the standard Feynman diagrams of the corresponding quantum field theory.
Non-planar one-loop Parke-Taylor factors in the CHY approach for quadratic propagators
NASA Astrophysics Data System (ADS)
Ahmadiniaz, Naser; Gomez, Humberto; Lopez-Arcos, Cristhiam
2018-05-01
In this work we have studied the Kleiss-Kuijf relations for the recently introduced Parke-Taylor factors at one-loop in the CHY approach, that reproduce quadratic Feynman propagators. By doing this, we were able to identify the non-planar one-loop Parke-Taylor factors. In order to check that, in fact, these new factors can describe non-planar amplitudes, we applied them to the bi-adjoint Φ3 theory. As a byproduct, we found a new type of graphs that we called the non-planar CHY-graphs. These graphs encode all the information for the subleading order at one-loop, and there is not an equivalent of these in the Feynman formalism.
An implementation of the look-ahead Lanczos algorithm for non-Hermitian matrices, part 2
NASA Technical Reports Server (NTRS)
Freund, Roland W.; Nachtigal, Noel M.
1990-01-01
It is shown how the look-ahead Lanczos process (combined with a quasi-minimal residual QMR) approach) can be used to develop a robust black box solver for large sparse non-Hermitian linear systems. Details of an implementation of the resulting QMR algorithm are presented. It is demonstrated that the QMR method is closely related to the biconjugate gradient (BCG) algorithm; however, unlike BCG, the QMR algorithm has smooth convergence curves and good numerical properties. We report numerical experiments with our implementation of the look-ahead Lanczos algorithm, both for eigenvalue problem and linear systems. Also, program listings of FORTRAN implementations of the look-ahead algorithm and the QMR method are included.
FPGA-based Klystron linearization implementations in scope of ILC
Omet, M.; Michizono, S.; Matsumoto, T.; ...
2015-01-23
We report the development and implementation of four FPGA-based predistortion-type klystron linearization algorithms. Klystron linearization is essential for the realization of ILC, since it is required to operate the klystrons 7% in power below their saturation. The work presented was performed in international collaborations at the Fermi National Accelerator Laboratory (FNAL), USA and the Deutsches Elektronen Synchrotron (DESY), Germany. With the newly developed algorithms, the generation of correction factors on the FPGA was improved compared to past algorithms, avoiding quantization and decreasing memory requirements. At FNAL, three algorithms were tested at the Advanced Superconducting Test Accelerator (ASTA), demonstrating a successfulmore » implementation for one algorithm and a proof of principle for two algorithms. Furthermore, the functionality of the algorithm implemented at DESY was demonstrated successfully in a simulation.« less
The implement of Talmud property allocation algorithm based on graphic point-segment way
NASA Astrophysics Data System (ADS)
Cen, Haifeng
2017-04-01
Under the guidance of the Talmud allocation scheme's theory, the paper analyzes the algorithm implemented process via the perspective of graphic point-segment way, and designs the point-segment way's Talmud property allocation algorithm. Then it uses Java language to implement the core of allocation algorithm, by using Android programming to build a visual interface.
A white noise approach to the Feynman integrand for electrons in random media
DOE Office of Scientific and Technical Information (OSTI.GOV)
Grothaus, M., E-mail: grothaus@mathematik.uni-kl.de; Riemann, F., E-mail: riemann@mathematik.uni-kl.de; Suryawan, H. P., E-mail: suryawan@mathematik.uni-kl.de
2014-01-15
Using the Feynman path integral representation of quantum mechanics it is possible to derive a model of an electron in a random system containing dense and weakly coupled scatterers [see F. Edwards and Y. B. Gulyaev, “The density of states of a highly impure semiconductor,” Proc. Phys. Soc. 83, 495–496 (1964)]. The main goal of this paper is to give a mathematically rigorous realization of the corresponding Feynman integrand in dimension one based on the theory of white noise analysis. We refine and apply a Wick formula for the product of a square-integrable function with Donsker's delta functions and usemore » a method of complex scaling. As an essential part of the proof we also establish the existence of the exponential of the self-intersection local times of a one-dimensional Brownian bridge. As a result we obtain a neat formula for the propagator with identical start and end point. Thus, we obtain a well-defined mathematical object which is used to calculate the density of states [see, e.g., F. Edwards and Y. B. Gulyaev, “The density of states of a highly impure semiconductor,” Proc. Phys. Soc. 83, 495–496 (1964)].« less
The SAPHIRE server: a new algorithm and implementation.
Hersh, W.; Leone, T. J.
1995-01-01
SAPHIRE is an experimental information retrieval system implemented to test new approaches to automated indexing and retrieval of medical documents. Due to limitations in its original concept-matching algorithm, a modified algorithm has been implemented which allows greater flexibility in partial matching and different word order within concepts. With the concomitant growth in client-server applications and the Internet in general, the new algorithm has been implemented as a server that can be accessed via other applications on the Internet. PMID:8563413
A cellular automata based FPGA realization of a new metaheuristic bat-inspired algorithm
NASA Astrophysics Data System (ADS)
Progias, Pavlos; Amanatiadis, Angelos A.; Spataro, William; Trunfio, Giuseppe A.; Sirakoulis, Georgios Ch.
2016-10-01
Optimization algorithms are often inspired by processes occuring in nature, such as animal behavioral patterns. The main concern with implementing such algorithms in software is the large amounts of processing power they require. In contrast to software code, that can only perform calculations in a serial manner, an implementation in hardware, exploiting the inherent parallelism of single-purpose processors, can prove to be much more efficient both in speed and energy consumption. Furthermore, the use of Cellular Automata (CA) in such an implementation would be efficient both as a model for natural processes, as well as a computational paradigm implemented well on hardware. In this paper, we propose a VHDL implementation of a metaheuristic algorithm inspired by the echolocation behavior of bats. More specifically, the CA model is inspired by the metaheuristic algorithm proposed earlier in the literature, which could be considered at least as efficient than other existing optimization algorithms. The function of the FPGA implementation of our algorithm is explained in full detail and results of our simulations are also demonstrated.
Categorizing Variations of Student-Implemented Sorting Algorithms
ERIC Educational Resources Information Center
Taherkhani, Ahmad; Korhonen, Ari; Malmi, Lauri
2012-01-01
In this study, we examined freshmen students' sorting algorithm implementations in data structures and algorithms' course in two phases: at the beginning of the course before the students received any instruction on sorting algorithms, and after taking a lecture on sorting algorithms. The analysis revealed that many students have insufficient…
An Agent Inspired Reconfigurable Computing Implementation of a Genetic Algorithm
NASA Technical Reports Server (NTRS)
Weir, John M.; Wells, B. Earl
2003-01-01
Many software systems have been successfully implemented using an agent paradigm which employs a number of independent entities that communicate with one another to achieve a common goal. The distributed nature of such a paradigm makes it an excellent candidate for use in high speed reconfigurable computing hardware environments such as those present in modem FPGA's. In this paper, a distributed genetic algorithm that can be applied to the agent based reconfigurable hardware model is introduced. The effectiveness of this new algorithm is evaluated by comparing the quality of the solutions found by the new algorithm with those found by traditional genetic algorithms. The performance of a reconfigurable hardware implementation of the new algorithm on an FPGA is compared to traditional single processor implementations.
Implementing a self-structuring data learning algorithm
NASA Astrophysics Data System (ADS)
Graham, James; Carson, Daniel; Ternovskiy, Igor
2016-05-01
In this paper, we elaborate on what we did to implement our self-structuring data learning algorithm. To recap, we are working to develop a data learning algorithm that will eventually be capable of goal driven pattern learning and extrapolation of more complex patterns from less complex ones. At this point we have developed a conceptual framework for the algorithm, but have yet to discuss our actual implementation and the consideration and shortcuts we needed to take to create said implementation. We will elaborate on our initial setup of the algorithm and the scenarios we used to test our early stage algorithm. While we want this to be a general algorithm, it is necessary to start with a simple scenario or two to provide a viable development and testing environment. To that end, our discussion will be geared toward what we include in our initial implementation and why, as well as what concerns we may have. In the future, we expect to be able to apply our algorithm to a more general approach, but to do so within a reasonable time, we needed to pick a place to start.
A sample implementation for parallelizing Divide-and-Conquer algorithms on the GPU.
Mei, Gang; Zhang, Jiayin; Xu, Nengxiong; Zhao, Kunyang
2018-01-01
The strategy of Divide-and-Conquer (D&C) is one of the frequently used programming patterns to design efficient algorithms in computer science, which has been parallelized on shared memory systems and distributed memory systems. Tzeng and Owens specifically developed a generic paradigm for parallelizing D&C algorithms on modern Graphics Processing Units (GPUs). In this paper, by following the generic paradigm proposed by Tzeng and Owens, we provide a new and publicly available GPU implementation of the famous D&C algorithm, QuickHull, to give a sample and guide for parallelizing D&C algorithms on the GPU. The experimental results demonstrate the practicality of our sample GPU implementation. Our research objective in this paper is to present a sample GPU implementation of a classical D&C algorithm to help interested readers to develop their own efficient GPU implementations with fewer efforts.
Parallel optimization algorithms and their implementation in VLSI design
NASA Technical Reports Server (NTRS)
Lee, G.; Feeley, J. J.
1991-01-01
Two new parallel optimization algorithms based on the simplex method are described. They may be executed by a SIMD parallel processor architecture and be implemented in VLSI design. Several VLSI design implementations are introduced. An application example is reported to demonstrate that the algorithms are effective.
Optimizing Approximate Weighted Matching on Nvidia Kepler K40
DOE Office of Scientific and Technical Information (OSTI.GOV)
Naim, Md; Manne, Fredrik; Halappanavar, Mahantesh
Matching is a fundamental graph problem with numerous applications in science and engineering. While algorithms for computing optimal matchings are difficult to parallelize, approximation algorithms on the other hand generally compute high quality solutions and are amenable to parallelization. In this paper, we present efficient implementations of the current best algorithm for half-approximate weighted matching, the Suitor algorithm, on Nvidia Kepler K-40 platform. We develop four variants of the algorithm that exploit hardware features to address key challenges for a GPU implementation. We also experiment with different combinations of work assigned to a warp. Using an exhaustive set ofmore » $269$ inputs, we demonstrate that the new implementation outperforms the previous best GPU algorithm by $10$ to $$100\\times$$ for over $100$ instances, and from $100$ to $$1000\\times$$ for $15$ instances. We also demonstrate up to $$20\\times$$ speedup relative to $2$ threads, and up to $$5\\times$$ relative to $16$ threads on Intel Xeon platform with $16$ cores for the same algorithm. The new algorithms and implementations provided in this paper will have a direct impact on several applications that repeatedly use matching as a key compute kernel. Further, algorithm designs and insights provided in this paper will benefit other researchers implementing graph algorithms on modern GPU architectures.« less
Overview of implementation of DARPA GPU program in SAIC
NASA Astrophysics Data System (ADS)
Braunreiter, Dennis; Furtek, Jeremy; Chen, Hai-Wen; Healy, Dennis
2008-04-01
This paper reviews the implementation of DARPA MTO STAP-BOY program for both Phase I and II conducted at Science Applications International Corporation (SAIC). The STAP-BOY program conducts fast covariance factorization and tuning techniques for space-time adaptive process (STAP) Algorithm Implementation on Graphics Processor unit (GPU) Architectures for Embedded Systems. The first part of our presentation on the DARPA STAP-BOY program will focus on GPU implementation and algorithm innovations for a prototype radar STAP algorithm. The STAP algorithm will be implemented on the GPU, using stream programming (from companies such as PeakStream, ATI Technologies' CTM, and NVIDIA) and traditional graphics APIs. This algorithm will include fast range adaptive STAP weight updates and beamforming applications, each of which has been modified to exploit the parallel nature of graphics architectures.
Correlation energy for elementary bosons: Physics of the singularity
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shiau, Shiue-Yuan, E-mail: syshiau@mail.ncku.edu.tw; Combescot, Monique; Chang, Yia-Chung, E-mail: yiachang@gate.sinica.edu.tw
2016-04-15
We propose a compact perturbative approach that reveals the physical origin of the singularity occurring in the density dependence of correlation energy: like fermions, elementary bosons have a singular correlation energy which comes from the accumulation, through Feynman “bubble” diagrams, of the same non-zero momentum transfer excitations from the free particle ground state, that is, the Fermi sea for fermions and the Bose–Einstein condensate for bosons. This understanding paves the way toward deriving the correlation energy of composite bosons like atomic dimers and semiconductor excitons, by suggesting Shiva diagrams that have similarity with Feynman “bubble” diagrams, the previous elementary bosonmore » approaches, which hide this physics, being inappropriate to do so.« less
Hopf algebras of rooted forests, cocyles, and free Rota-Baxter algebras
NASA Astrophysics Data System (ADS)
Zhang, Tianjie; Gao, Xing; Guo, Li
2016-10-01
The Hopf algebra and the Rota-Baxter algebra are the two algebraic structures underlying the algebraic approach of Connes and Kreimer to renormalization of perturbative quantum field theory. In particular, the Hopf algebra of rooted trees serves as the "baby model" of Feynman graphs in their approach and can be characterized by certain universal properties involving a Hochschild 1-cocycle. Decorated rooted trees have also been applied to study Feynman graphs. We will continue the study of universal properties of various spaces of decorated rooted trees with such a 1-cocycle, leading to the concept of a cocycle Hopf algebra. We further apply the universal properties to equip a free Rota-Baxter algebra with the structure of a cocycle Hopf algebra.
NASA Astrophysics Data System (ADS)
Baaquie, Belal E.
2007-01-01
European options on coupon bonds are studied in a quantum field theory model of forward interest rates. Swaptions are briefly reviewed. An approximation scheme for the coupon bond option price is developed based on the fact that the volatility of the forward interest rates is a small quantity. The field theory for the forward interest rates is Gaussian, but when the payoff function for the coupon bond option is included it makes the field theory nonlocal and nonlinear. A perturbation expansion using Feynman diagrams gives a closed form approximation for the price of coupon bond option. A special case of the approximate bond option is shown to yield the industry standard one-factor HJM formula with exponential volatility.
Solution of a cauchy problem for a diffusion equation in a Hilbert space by a Feynman formula
NASA Astrophysics Data System (ADS)
Remizov, I. D.
2012-07-01
The Cauchy problem for a class of diffusion equations in a Hilbert space is studied. It is proved that the Cauchy problem in well posed in the class of uniform limits of infinitely smooth bounded cylindrical functions on the Hilbert space, and the solution is presented in the form of the so-called Feynman formula, i.e., a limit of multiple integrals against a gaussian measure as the multiplicity tends to infinity. It is also proved that the solution of the Cauchy problem depends continuously on the diffusion coefficient. A process reducing an approximate solution of an infinite-dimensional diffusion equation to finding a multiple integral of a real function of finitely many real variables is indicated.
Feynman propagator for spin foam quantum gravity.
Oriti, Daniele
2005-03-25
We link the notion causality with the orientation of the spin foam 2-complex. We show that all current spin foam models are orientation independent. Using the technology of evolution kernels for quantum fields on Lie groups, we construct a generalized version of spin foam models, introducing an extra proper time variable. We prove that different ranges of integration for this variable lead to different classes of spin foam models: the usual ones, interpreted as the quantum gravity analogue of the Hadamard function of quantum field theory (QFT) or as inner products between quantum gravity states; and a new class of causal models, the quantum gravity analogue of the Feynman propagator in QFT, nontrivial function of the orientation data, and implying a notion of "timeless ordering".
Baaquie, Belal E
2007-01-01
European options on coupon bonds are studied in a quantum field theory model of forward interest rates. Swaptions are briefly reviewed. An approximation scheme for the coupon bond option price is developed based on the fact that the volatility of the forward interest rates is a small quantity. The field theory for the forward interest rates is Gaussian, but when the payoff function for the coupon bond option is included it makes the field theory nonlocal and nonlinear. A perturbation expansion using Feynman diagrams gives a closed form approximation for the price of coupon bond option. A special case of the approximate bond option is shown to yield the industry standard one-factor HJM formula with exponential volatility.
Tsuruta, S; Misztal, I; Strandén, I
2001-05-01
Utility of the preconditioned conjugate gradient algorithm with a diagonal preconditioner for solving mixed-model equations in animal breeding applications was evaluated with 16 test problems. The problems included single- and multiple-trait analyses, with data on beef, dairy, and swine ranging from small examples to national data sets. Multiple-trait models considered low and high genetic correlations. Convergence was based on relative differences between left- and right-hand sides. The ordering of equations was fixed effects followed by random effects, with no special ordering within random effects. The preconditioned conjugate gradient program implemented with double precision converged for all models. However, when implemented in single precision, the preconditioned conjugate gradient algorithm did not converge for seven large models. The preconditioned conjugate gradient and successive overrelaxation algorithms were subsequently compared for 13 of the test problems. The preconditioned conjugate gradient algorithm was easy to implement with the iteration on data for general models. However, successive overrelaxation requires specific programming for each set of models. On average, the preconditioned conjugate gradient algorithm converged in three times fewer rounds of iteration than successive overrelaxation. With straightforward implementations, programs using the preconditioned conjugate gradient algorithm may be two or more times faster than those using successive overrelaxation. However, programs using the preconditioned conjugate gradient algorithm would use more memory than would comparable implementations using successive overrelaxation. Extensive optimization of either algorithm can influence rankings. The preconditioned conjugate gradient implemented with iteration on data, a diagonal preconditioner, and in double precision may be the algorithm of choice for solving mixed-model equations when sufficient memory is available and ease of implementation is essential.
A general heuristic for genome rearrangement problems.
Dias, Ulisses; Galvão, Gustavo Rodrigues; Lintzmayer, Carla Négri; Dias, Zanoni
2014-06-01
In this paper, we present a general heuristic for several problems in the genome rearrangement field. Our heuristic does not solve any problem directly, it is rather used to improve the solutions provided by any non-optimal algorithm that solve them. Therefore, we have implemented several algorithms described in the literature and several algorithms developed by ourselves. As a whole, we implemented 23 algorithms for 9 well known problems in the genome rearrangement field. A total of 13 algorithms were implemented for problems that use the notions of prefix and suffix operations. In addition, we worked on 5 algorithms for the classic problem of sorting by transposition and we conclude the experiments by presenting results for 3 approximation algorithms for the sorting by reversals and transpositions problem and 2 approximation algorithms for the sorting by reversals problem. Another algorithm with better approximation ratio can be found for the last genome rearrangement problem, but it is purely theoretical with no practical implementation. The algorithms we implemented in addition to our heuristic lead to the best practical results in each case. In particular, we were able to improve results on the sorting by transpositions problem, which is a very special case because many efforts have been made to generate algorithms with good results in practice and some of these algorithms provide results that equal the optimum solutions in many cases. Our source codes and benchmarks are freely available upon request from the authors so that it will be easier to compare new approaches against our results.
Implementation and performance evaluation of acoustic denoising algorithms for UAV
NASA Astrophysics Data System (ADS)
Chowdhury, Ahmed Sony Kamal
Unmanned Aerial Vehicles (UAVs) have become popular alternative for wildlife monitoring and border surveillance applications. Elimination of the UAV's background noise and classifying the target audio signal effectively are still a major challenge. The main goal of this thesis is to remove UAV's background noise by means of acoustic denoising techniques. Existing denoising algorithms, such as Adaptive Least Mean Square (LMS), Wavelet Denoising, Time-Frequency Block Thresholding, and Wiener Filter, were implemented and their performance evaluated. The denoising algorithms were evaluated for average Signal to Noise Ratio (SNR), Segmental SNR (SSNR), Log Likelihood Ratio (LLR), and Log Spectral Distance (LSD) metrics. To evaluate the effectiveness of the denoising algorithms on classification of target audio, we implemented Support Vector Machine (SVM) and Naive Bayes classification algorithms. Simulation results demonstrate that LMS and Discrete Wavelet Transform (DWT) denoising algorithm offered superior performance than other algorithms. Finally, we implemented the LMS and DWT algorithms on a DSP board for hardware evaluation. Experimental results showed that LMS algorithm's performance is robust compared to DWT for various noise types to classify target audio signals.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Omet, M.; Michizono, S.; Matsumoto, T.
We report the development and implementation of four FPGA-based predistortion-type klystron linearization algorithms. Klystron linearization is essential for the realization of ILC, since it is required to operate the klystrons 7% in power below their saturation. The work presented was performed in international collaborations at the Fermi National Accelerator Laboratory (FNAL), USA and the Deutsches Elektronen Synchrotron (DESY), Germany. With the newly developed algorithms, the generation of correction factors on the FPGA was improved compared to past algorithms, avoiding quantization and decreasing memory requirements. At FNAL, three algorithms were tested at the Advanced Superconducting Test Accelerator (ASTA), demonstrating a successfulmore » implementation for one algorithm and a proof of principle for two algorithms. Furthermore, the functionality of the algorithm implemented at DESY was demonstrated successfully in a simulation.« less
Deptuch, Grzegorz W.; Fahim, Farah; Grybos, Pawel; ...
2017-06-28
An on-chip implementable algorithm for allocation of an X-ray photon imprint, called a hit, to a single pixel in the presence of charge sharing in a highly segmented pixel detector is described. Its proof-of-principle implementation is also given supported by the results of tests using a highly collimated X-ray photon beam from a synchrotron source. The algorithm handles asynchronous arrivals of X-ray photons. Activation of groups of pixels, comparisons of peak amplitudes of pulses within an active neighborhood and finally latching of the results of these comparisons constitute the three procedural steps of the algorithm. A grouping of pixels tomore » one virtual pixel, that recovers composite signals and event driven strobes, to control comparisons of fractional signals between neighboring pixels are the actuators of the algorithm. The circuitry necessary to implement the algorithm requires an extensive inter-pixel connection grid of analog and digital signals, that are exchanged between pixels. A test-circuit implementation of the algorithm was achieved with a small array of 32 × 32 pixels and the device was exposed to an 8 keV highly collimated to a diameter of 3-μm X-ray beam. Furthermore, the results of these tests are given in this paper assessing physical implementation of the algorithm.« less
Chiral limit of N = 4 SYM and ABJM and integrable Feynman graphs
NASA Astrophysics Data System (ADS)
Caetano, João; Gürdoğan, Ömer; Kazakov, Vladimir
2018-03-01
We consider a special double scaling limit, recently introduced by two of the authors, combining weak coupling and large imaginary twist, for the γ-twisted N = 4 SYM theory. We also establish the analogous limit for ABJM theory. The resulting non-gauge chiral 4D and 3D theories of interacting scalars and fermions are integrable in the planar limit. In spite of the breakdown of conformality by double-trace interactions, most of the correlators for local operators of these theories are conformal, with non-trivial anomalous dimensions defined by specific, integrable Feynman diagrams. We discuss the details of this diagrammatics. We construct the doubly-scaled asymptotic Bethe ansatz (ABA) equations for multi-magnon states in these theories. Each entry of the mixing matrix of local conformal operators in the simplest of these theories — the bi-scalar model in 4D and tri-scalar model in 3D — is given by a single Feynman diagram at any given loop order. The related diagrams are in principle computable, up to a few scheme dependent constants, by integrability methods (quantum spectral curve or ABA). These constants should be fixed from direct computations of a few simplest graphs. This integrability-based method is advocated to be able to provide information about some high loop order graphs which are hardly computable by other known methods. We exemplify our approach with specific five-loop graphs.
NMR implementation of adiabatic SAT algorithm using strongly modulated pulses.
Mitra, Avik; Mahesh, T S; Kumar, Anil
2008-03-28
NMR implementation of adiabatic algorithms face severe problems in homonuclear spin systems since the qubit selective pulses are long and during this period, evolution under the Hamiltonian and decoherence cause errors. The decoherence destroys the answer as it causes the final state to evolve to mixed state and in homonuclear systems, evolution under the internal Hamiltonian causes phase errors preventing the initial state to converge to the solution state. The resolution of these issues is necessary before one can proceed to implement an adiabatic algorithm in a large system where homonuclear coupled spins will become a necessity. In the present work, we demonstrate that by using "strongly modulated pulses" (SMPs) for the creation of interpolating Hamiltonian, one can circumvent both the problems and successfully implement the adiabatic SAT algorithm in a homonuclear three qubit system. This work also demonstrates that the SMPs tremendously reduce the time taken for the implementation of the algorithm, can overcome problems associated with decoherence, and will be the modality in future implementation of quantum information processing by NMR.
Digital signal processing algorithms for automatic voice recognition
NASA Technical Reports Server (NTRS)
Botros, Nazeih M.
1987-01-01
The current digital signal analysis algorithms are investigated that are implemented in automatic voice recognition algorithms. Automatic voice recognition means, the capability of a computer to recognize and interact with verbal commands. The digital signal is focused on, rather than the linguistic, analysis of speech signal. Several digital signal processing algorithms are available for voice recognition. Some of these algorithms are: Linear Predictive Coding (LPC), Short-time Fourier Analysis, and Cepstrum Analysis. Among these algorithms, the LPC is the most widely used. This algorithm has short execution time and do not require large memory storage. However, it has several limitations due to the assumptions used to develop it. The other 2 algorithms are frequency domain algorithms with not many assumptions, but they are not widely implemented or investigated. However, with the recent advances in the digital technology, namely signal processors, these 2 frequency domain algorithms may be investigated in order to implement them in voice recognition. This research is concerned with real time, microprocessor based recognition algorithms.
Motion Cueing Algorithm Development: New Motion Cueing Program Implementation and Tuning
NASA Technical Reports Server (NTRS)
Houck, Jacob A. (Technical Monitor); Telban, Robert J.; Cardullo, Frank M.; Kelly, Lon C.
2005-01-01
A computer program has been developed for the purpose of driving the NASA Langley Research Center Visual Motion Simulator (VMS). This program includes two new motion cueing algorithms, the optimal algorithm and the nonlinear algorithm. A general description of the program is given along with a description and flowcharts for each cueing algorithm, and also descriptions and flowcharts for subroutines used with the algorithms. Common block variable listings and a program listing are also provided. The new cueing algorithms have a nonlinear gain algorithm implemented that scales each aircraft degree-of-freedom input with a third-order polynomial. A description of the nonlinear gain algorithm is given along with past tuning experience and procedures for tuning the gain coefficient sets for each degree-of-freedom to produce the desired piloted performance. This algorithm tuning will be needed when the nonlinear motion cueing algorithm is implemented on a new motion system in the Cockpit Motion Facility (CMF) at the NASA Langley Research Center.
Khatua, Pradip; Bansal, Bhavtosh; Shahar, Dan
2014-01-10
In a "thought experiment," now a classic in physics pedagogy, Feynman visualizes Young's double-slit interference experiment with electrons in magnetic field. He shows that the addition of an Aharonov-Bohm phase is equivalent to shifting the zero-field wave interference pattern by an angle expected from the Lorentz force calculation for classical particles. We have performed this experiment with one slit, instead of two, where ballistic electrons within two-dimensional electron gas diffract through a small orifice formed by a quantum point contact (QPC). As the QPC width is comparable to the electron wavelength, the observed intensity profile is further modulated by the transverse waveguide modes present at the injector QPC. Our experiments open the way to realizing diffraction-based ideas in mesoscopic physics.
Using an atom interferometer to take the Gedanken out of Feynman's Gedankenexperiment
NASA Astrophysics Data System (ADS)
Pritchard, David E.; Hammond, Troy D.; Lenef, Alan; Rubenstein, Richard A.; Smith, Edward T.; Chapman, Michael S.; Schmiedmayer, Jörg
1997-01-01
We give a description of two experiments performed in an atom interferometer at MIT. By scattering a single photon off of the atom as it passes through the interferometer, we perform a version of a classic gedankenexperiment, a demonstration of a Feynman light microscope. As path information about the atom is gained, contrast in the atom fringes (coherence) is lost. The lost coherence is then recovered by observing only atoms which scatter photons into a particular final direction. This paper reflects the main emphasis of D. E. Pritchard's talk at the RIS meeting. Information about other topics covered in that talk, as well as a review of all of the published work performed with the MIT atom/molecule interferometer, is available on the world wide web at http://coffee.mit.edu/.
Critical exponents for diluted resistor networks
NASA Astrophysics Data System (ADS)
Stenull, O.; Janssen, H. K.; Oerding, K.
1999-05-01
An approach by Stephen [Phys. Rev. B 17, 4444 (1978)] is used to investigate the critical properties of randomly diluted resistor networks near the percolation threshold by means of renormalized field theory. We reformulate an existing field theory by Harris and Lubensky [Phys. Rev. B 35, 6964 (1987)]. By a decomposition of the principal Feynman diagrams, we obtain diagrams which again can be interpreted as resistor networks. This interpretation provides for an alternative way of evaluating the Feynman diagrams for random resistor networks. We calculate the resistance crossover exponent φ up to second order in ɛ=6-d, where d is the spatial dimension. Our result φ=1+ɛ/42+4ɛ2/3087 verifies a previous calculation by Lubensky and Wang, which itself was based on the Potts-model formulation of the random resistor network.
Multiple Lookup Table-Based AES Encryption Algorithm Implementation
NASA Astrophysics Data System (ADS)
Gong, Jin; Liu, Wenyi; Zhang, Huixin
Anew AES (Advanced Encryption Standard) encryption algorithm implementation was proposed in this paper. It is based on five lookup tables, which are generated from S-box(the substitution table in AES). The obvious advantages are reducing the code-size, improving the implementation efficiency, and helping new learners to understand the AES encryption algorithm and GF(28) multiplication which are necessary to correctly implement AES[1]. This method can be applied on processors with word length 32 or above, FPGA and others. And correspondingly we can implement it by VHDL, Verilog, VB and other languages.
NASA Technical Reports Server (NTRS)
Vo, San C.; Biegel, Bryan (Technical Monitor)
2001-01-01
Scalar multiplication is an essential operation in elliptic curve cryptosystems because its implementation determines the speed and the memory storage requirements. This paper discusses some improvements on two popular signed window algorithms for implementing scalar multiplications of an elliptic curve point - Morain-Olivos's algorithm and Koyarna-Tsuruoka's algorithm.
Implementation of an Algorithm for Prosthetic Joint Infection: Deviations and Problems.
Mühlhofer, Heinrich M L; Kanz, Karl-Georg; Pohlig, Florian; Lenze, Ulrich; Lenze, Florian; Toepfer, Andreas; von Eisenhart-Rothe, Ruediger; Schauwecker, Johannes
The outcome of revision surgery in arthroplasty is based on a precise diagnosis. In addition, the treatment varies based on whether the prosthetic failure is caused by aseptic or septic loosening. Algorithms can help to identify periprosthetic joint infections (PJI) and standardize diagnostic steps, however, algorithms tend to oversimplify the treatment of complex cases. We conducted a process analysis during the implementation of a PJI algorithm to determine problems and deviations associated with the implementation of this algorithm. Fifty patients who were treated after implementing a standardized algorithm were monitored retrospectively. Their treatment plans and diagnostic cascades were analyzed for deviations from the implemented algorithm. Each diagnostic procedure was recorded, compared with the algorithm, and evaluated statistically. We detected 52 deviations while treating 50 patients. In 25 cases, no discrepancy was observed. Synovial fluid aspiration was not performed in 31.8% of patients (95% confidence interval [CI], 18.1%-45.6%), while white blood cell counts (WBCs) and neutrophil differentiation were assessed in 54.5% of patients (95% CI, 39.8%-69.3%). We also observed that the prolonged incubation of cultures was not requested in 13.6% of patients (95% CI, 3.5%-23.8%). In seven of 13 cases (63.6%; 95% CI, 35.2%-92.1%), arthroscopic biopsy was performed; 6 arthroscopies were performed in discordance with the algorithm (12%; 95% CI, 3%-21%). Self-critical analysis of diagnostic processes and monitoring of deviations using algorithms are important and could increase the quality of treatment by revealing recurring faults.
A GPU-paralleled implementation of an enhanced face recognition algorithm
NASA Astrophysics Data System (ADS)
Chen, Hao; Liu, Xiyang; Shao, Shuai; Zan, Jiguo
2013-03-01
Face recognition algorithm based on compressed sensing and sparse representation is hotly argued in these years. The scheme of this algorithm increases recognition rate as well as anti-noise capability. However, the computational cost is expensive and has become a main restricting factor for real world applications. In this paper, we introduce a GPU-accelerated hybrid variant of face recognition algorithm named parallel face recognition algorithm (pFRA). We describe here how to carry out parallel optimization design to take full advantage of many-core structure of a GPU. The pFRA is tested and compared with several other implementations under different data sample size. Finally, Our pFRA, implemented with NVIDIA GPU and Computer Unified Device Architecture (CUDA) programming model, achieves a significant speedup over the traditional CPU implementations.
Fourth-order self-energy contribution to the two loop Lamb shift
NASA Astrophysics Data System (ADS)
Palur Mallampalli, Subrahmanyam
1998-11-01
The calculation of the two loop Lamb shift in hydrogenic ions involves the numerical evaluation of ten Feynman diagrams. In this thesis, four fourth-order Feynman diagrams including the pure self-energy contributions are evaluated using exact Dirac-Coulomb propagators, so that higher order binding corrections can be extracted by comparing with the known terms in the Z/alpha expansion. The entire calculation is performed in Feynman gauge. One of the vacuum polarization diagrams is evaluated in the Uehling approximation. At low Z, it is seen to be perturbative in Z/alpha, while new predictions for high Z are made. The calculation of the three self-energy diagrams is reorganized into four terms, which we call the PO, M, F and P terms. The PO term is separately gauge invariant while the latter three form a gauge invariant set. The PO term is shown to exhibit the most non-perturbative behavior yet encountered in QED at low Z, so much so that even at Z = 1, the complete result is of the opposite sign as that of the leading term in its Z/alpha expansion. At high Z, we agree with an earlier calculation. The analysis of ultraviolet divergences in the two loop self-energy is complicated by the presence of sub- divergences. All divergences except the self-mass are shown to cancel. The self-mass is then removed by a self- mass counterterm. Parts of the calculation are shown to contain reference state singularities, that finally cancel. A numerical regulator to handle these singularities is described. The M term, an ultraviolet finite quantity, is defined through a subtraction scheme in coordinate space. Being computationally intensive, it is evaluated only at high Z, specifically Z = 83 and 92. The F term involves the evaluation of several Feynman diagrams with free electron propagators. These are computed for a range of values of Z. The P term, also ultraviolet finite, involves Dirac- Coulomb propagators that are best defined in coordinate space, as well as functions associated with the one loop self-energy that are best defined in momentum space. Possible methods of evaluating the P term are discussed.
Introducing parallelism to histogramming functions for GEM systems
NASA Astrophysics Data System (ADS)
Krawczyk, Rafał D.; Czarski, Tomasz; Kolasinski, Piotr; Pozniak, Krzysztof T.; Linczuk, Maciej; Byszuk, Adrian; Chernyshova, Maryna; Juszczyk, Bartlomiej; Kasprowicz, Grzegorz; Wojenski, Andrzej; Zabolotny, Wojciech
2015-09-01
This article is an assessment of potential parallelization of histogramming algorithms in GEM detector system. Histogramming and preprocessing algorithms in MATLAB were analyzed with regard to adding parallelism. Preliminary implementation of parallel strip histogramming resulted in speedup. Analysis of algorithms parallelizability is presented. Overview of potential hardware and software support to implement parallel algorithm is discussed.
Sample-Based Motion Planning in High-Dimensional and Differentially-Constrained Systems
2010-02-01
Reachable Set . . . 88 6-1 LittleDog Robot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 6-2 Dog bounding up stairs ...planning algorithm implemented on LittleDog, a quadruped robot . The motion planning algorithm successfully planned bounding trajectories over extremely...a motion planning algorithm implemented on LittleDog, a quadruped robot . The motion planning algorithm successfully planned bounding trajectories
Parallel asynchronous systems and image processing algorithms
NASA Technical Reports Server (NTRS)
Coon, D. D.; Perera, A. G. U.
1989-01-01
A new hardware approach to implementation of image processing algorithms is described. The approach is based on silicon devices which would permit an independent analog processing channel to be dedicated to evey pixel. A laminar architecture consisting of a stack of planar arrays of the device would form a two-dimensional array processor with a 2-D array of inputs located directly behind a focal plane detector array. A 2-D image data stream would propagate in neuronlike asynchronous pulse coded form through the laminar processor. Such systems would integrate image acquisition and image processing. Acquisition and processing would be performed concurrently as in natural vision systems. The research is aimed at implementation of algorithms, such as the intensity dependent summation algorithm and pyramid processing structures, which are motivated by the operation of natural vision systems. Implementation of natural vision algorithms would benefit from the use of neuronlike information coding and the laminar, 2-D parallel, vision system type architecture. Besides providing a neural network framework for implementation of natural vision algorithms, a 2-D parallel approach could eliminate the serial bottleneck of conventional processing systems. Conversion to serial format would occur only after raw intensity data has been substantially processed. An interesting challenge arises from the fact that the mathematical formulation of natural vision algorithms does not specify the means of implementation, so that hardware implementation poses intriguing questions involving vision science.
Implementation of a partitioned algorithm for simulation of large CSI problems
NASA Technical Reports Server (NTRS)
Alvin, Kenneth F.; Park, K. C.
1991-01-01
The implementation of a partitioned numerical algorithm for determining the dynamic response of coupled structure/controller/estimator finite-dimensional systems is reviewed. The partitioned approach leads to a set of coupled first and second-order linear differential equations which are numerically integrated with extrapolation and implicit step methods. The present software implementation, ACSIS, utilizes parallel processing techniques at various levels to optimize performance on a shared-memory concurrent/vector processing system. A general procedure for the design of controller and filter gains is also implemented, which utilizes the vibration characteristics of the structure to be solved. Also presented are: example problems; a user's guide to the software; the procedures and algorithm scripts; a stability analysis for the algorithm; and the source code for the parallel implementation.
Scenario Decomposition for 0-1 Stochastic Programs: Improvements and Asynchronous Implementation
Ryan, Kevin; Rajan, Deepak; Ahmed, Shabbir
2016-05-01
We recently proposed scenario decomposition algorithm for stochastic 0-1 programs finds an optimal solution by evaluating and removing individual solutions that are discovered by solving scenario subproblems. In our work, we develop an asynchronous, distributed implementation of the algorithm which has computational advantages over existing synchronous implementations of the algorithm. Improvements to both the synchronous and asynchronous algorithm are proposed. We also test the results on well known stochastic 0-1 programs from the SIPLIB test library and is able to solve one previously unsolved instance from the test set.
Implementation of Multispectral Image Classification on a Remote Adaptive Computer
NASA Technical Reports Server (NTRS)
Figueiredo, Marco A.; Gloster, Clay S.; Stephens, Mark; Graves, Corey A.; Nakkar, Mouna
1999-01-01
As the demand for higher performance computers for the processing of remote sensing science algorithms increases, the need to investigate new computing paradigms its justified. Field Programmable Gate Arrays enable the implementation of algorithms at the hardware gate level, leading to orders of m a,gnitude performance increase over microprocessor based systems. The automatic classification of spaceborne multispectral images is an example of a computation intensive application, that, can benefit from implementation on an FPGA - based custom computing machine (adaptive or reconfigurable computer). A probabilistic neural network is used here to classify pixels of of a multispectral LANDSAT-2 image. The implementation described utilizes Java client/server application programs to access the adaptive computer from a remote site. Results verify that a remote hardware version of the algorithm (implemented on an adaptive computer) is significantly faster than a local software version of the same algorithm implemented on a typical general - purpose computer).
Simulation of n-qubit quantum systems. I. Quantum registers and quantum gates
NASA Astrophysics Data System (ADS)
Radtke, T.; Fritzsche, S.
2005-12-01
During recent years, quantum computations and the study of n-qubit quantum systems have attracted a lot of interest, both in theory and experiment. Apart from the promise of performing quantum computations, however, these investigations also revealed a great deal of difficulties which still need to be solved in practice. In quantum computing, unitary and non-unitary quantum operations act on a given set of qubits to form (entangled) states, in which the information is encoded by the overall system often referred to as quantum registers. To facilitate the simulation of such n-qubit quantum systems, we present the FEYNMAN program to provide all necessary tools in order to define and to deal with quantum registers and quantum operations. Although the present version of the program is restricted to unitary transformations, it equally supports—whenever possible—the representation of the quantum registers both, in terms of their state vectors and density matrices. In addition to the composition of two or more quantum registers, moreover, the program also supports their decomposition into various parts by applying the partial trace operation and the concept of the reduced density matrix. Using an interactive design within the framework of MAPLE, therefore, we expect the FEYNMAN program to be helpful not only for teaching the basic elements of quantum computing but also for studying their physical realization in the future. Program summaryTitle of program:FEYNMAN Catalogue number:ADWE Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADWE Program obtainable from:CPC Program Library, Queen's University of Belfast, N. Ireland Licensing provisions:None Computers for which the program is designed:All computers with a license of the computer algebra system MAPLE [Maple is a registered trademark of Waterlo Maple Inc.] Operating systems or monitors under which the program has been tested:Linux, MS Windows XP Programming language used:MAPLE 9.5 (but should be compatible with 9.0 and 8.0, too) Memory and time required to execute with typical data:Storage and time requirements critically depend on the number of qubits, n, in the quantum registers due to the exponential increase of the associated Hilbert space. In particular, complex algebraic operations may require large amounts of memory even for small qubit numbers. However, most of the standard commands (see Section 4 for simple examples) react promptly for up to five qubits on a normal single-processor machine ( ⩾1GHz with 512 MB memory) and use less than 10 MB memory. No. of lines in distributed program, including test data, etc.: 8864 No. of bytes in distributed program, including test data, etc.: 493 182 Distribution format: tar.gz Nature of the physical problem:During the last decade, quantum computing has been found to provide a revolutionary new form of computation. The algorithms by Shor [P.W. Shor, SIAM J. Sci. Statist. Comput. 26 (1997) 1484] and Grover [L.K. Grover, Phys. Rev. Lett. 79 (1997) 325. [2
Variational Principles, Occam Razor and Simplicity Paradox
NASA Astrophysics Data System (ADS)
Berezin, Alexander A.
2004-05-01
Variational minimum principles (VMP) refer to energy (statics, Thomson and Earnshaw theorems in electrostatics), action (Maupertuis, Euler, Lagrange, Hamilton), light (Fermat), quantum paths (Feynman), etc. Historically, VMP appeal to some economy in nature, similarly to Occam Razor Parsimony (ORP) principle. Version of ORP are "best world" (Leibniz), Panglossianism (Voltaire), and "most interesting world" (Dyson). Conceptually, VMP exemplify curious fact that infinite set is often simpler than its subsets (e.g., set of all integers is simpler than set of primes). Algorithmically very simple number 0.1234567... (Champernowne constant) contains Library of Babel of "all books" (Borges) and codes (infinitely many times) everything countably possible. Likewise, full Megaverse (Everett, Deutsch, Guth, Linde) is simpler than our specific ("Big Bang") universe. Dynamically, VMP imply memory effects akin to hysteresis. Similar ideas are "water memory" (Benveniste, Josephson) and isotopic biology (Berezin). Paradoxically, while ORP calls for economy (simplicity), unfolding of ORP in VMP seemingly works in the opposite direction allowing for complexity emergence (e.g., symmetry breaking in Jahn-Teller effect). Metaphysical extrapolation of this complimentarity may lead to "it-from-bit" (Wheeler) reflection of why there is something rather than nothing.
Massively parallel algorithms for real-time wavefront control of a dense adaptive optics system
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fijany, A.; Milman, M.; Redding, D.
1994-12-31
In this paper massively parallel algorithms and architectures for real-time wavefront control of a dense adaptive optic system (SELENE) are presented. The authors have already shown that the computation of a near optimal control algorithm for SELENE can be reduced to the solution of a discrete Poisson equation on a regular domain. Although, this represents an optimal computation, due the large size of the system and the high sampling rate requirement, the implementation of this control algorithm poses a computationally challenging problem since it demands a sustained computational throughput of the order of 10 GFlops. They develop a novel algorithm,more » designated as Fast Invariant Imbedding algorithm, which offers a massive degree of parallelism with simple communication and synchronization requirements. Due to these features, this algorithm is significantly more efficient than other Fast Poisson Solvers for implementation on massively parallel architectures. The authors also discuss two massively parallel, algorithmically specialized, architectures for low-cost and optimal implementation of the Fast Invariant Imbedding algorithm.« less
Ren, Shanshan; Bertels, Koen; Al-Ars, Zaid
2018-01-01
GATK HaplotypeCaller (HC) is a popular variant caller, which is widely used to identify variants in complex genomes. However, due to its high variants detection accuracy, it suffers from long execution time. In GATK HC, the pair-HMMs forward algorithm accounts for a large percentage of the total execution time. This article proposes to accelerate the pair-HMMs forward algorithm on graphics processing units (GPUs) to improve the performance of GATK HC. This article presents several GPU-based implementations of the pair-HMMs forward algorithm. It also analyzes the performance bottlenecks of the implementations on an NVIDIA Tesla K40 card with various data sets. Based on these results and the characteristics of GATK HC, we are able to identify the GPU-based implementations with the highest performance for the various analyzed data sets. Experimental results show that the GPU-based implementations of the pair-HMMs forward algorithm achieve a speedup of up to 5.47× over existing GPU-based implementations.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stevens, K; Huang, T; Buttler, D
We present the C-Cat Wordnet package, an open source library for using and modifying Wordnet. The package includes four key features: an API for modifying Synsets; implementations of standard similarity metrics, implementations of well known Word Sense Disambiguation algorithms, and an implementation of the Castanet algorithm. The library is easily extendible and usable in many runtime environments. We demonstrate it's use on two standard Word Sense Disambiguation tasks and apply the Castanet algorithm to a corpus.
Secret Key Crypto Implementations
NASA Astrophysics Data System (ADS)
Bertoni, Guido Marco; Melzani, Filippo
This chapter presents the algorithm selected in 2001 as the Advanced Encryption Standard. This algorithm is the base for implementing security and privacy based on symmetric key solutions in almost all new applications. Secret key algorithms are used in combination with modes of operation to provide different security properties. The most used modes of operation are presented in this chapter. Finally an overview of the different techniques of software and hardware implementations is given.
NASA Astrophysics Data System (ADS)
Liu, J.; Lu, W. Q.
2010-03-01
This paper presents the detailed MD simulation on the properties including the thermal conductivities and viscosities of the quantum fluid helium at different state points. The molecular interactions are represented by the Lennard-Jones pair potentials supplemented by quantum corrections following the Feynman-Hibbs approach and the properties are calculated using the Green-Kubo equations. A comparison is made among the numerical results using LJ and QFH potentials and the existing database and shows that the LJ model is not quantitatively correct for the supercritical liquid helium, thereby the quantum effect must be taken into account when the quantum fluid helium is studied. The comparison of the thermal conductivity is also made as a function of temperatures and pressure and the results show quantum effect correction is an efficient tool to get the thermal conductivities.
NASA Astrophysics Data System (ADS)
Goyal, Ketan; Kawai, Ryoichi
As nanotechnology advances, understanding of the thermodynamic properties of small systems becomes increasingly important. Such systems are found throughout physics, biology, and chemistry manifesting striking properties that are a direct result of their small dimensions where fluctuations become predominant. The standard theory of thermodynamics for macroscopic systems is powerless for such ever fluctuating systems. Furthermore, as small systems are inherently quantum mechanical, influence of quantum effects such as discreteness and quantum entanglement on their thermodynamic properties is of great interest. In particular, the quantum fluctuations due to quantum uncertainty principles may play a significant role. In this talk, we investigate thermodynamic properties of an autonomous quantum heat engine, resembling a quantum version of the Feynman Ratchet, in non-equilibrium condition based on the theory of open quantum systems. The heat engine consists of multiple subsystems individually contacted to different thermal environments.
Nonperturbative dynamics of scalar field theories through the Feynman-Schwinger representation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cetin Savkli; Franz Gross; John Tjon
2004-04-01
In this paper we present a summary of results obtained for scalar field theories using the Feynman-Schwinger (FSR) approach. Specifically, scalar QED and {chi}{sup 2}{phi} theories are considered. The motivation behind the applications discussed in this paper is to use the FSR method as a rigorous tool for testing the quality of commonly used approximations in field theory. Exact calculations in a quenched theory are presented for one-, two-, and three-body bound states. Results obtained indicate that some of the commonly used approximations, such as Bethe-Salpeter ladder summation for bound states and the rainbow summation for one body problems, producemore » significantly different results from those obtained from the FSR approach. We find that more accurate results can be obtained using other, simpler, approximation schemes.« less
Finally making sense of the double-slit experiment.
Aharonov, Yakir; Cohen, Eliahu; Colombo, Fabrizio; Landsberger, Tomer; Sabadini, Irene; Struppa, Daniele C; Tollaksen, Jeff
2017-06-20
Feynman stated that the double-slit experiment "…has in it the heart of quantum mechanics. In reality, it contains the only mystery" and that "nobody can give you a deeper explanation of this phenomenon than I have given; that is, a description of it" [Feynman R, Leighton R, Sands M (1965) The Feynman Lectures on Physics ]. We rise to the challenge with an alternative to the wave function-centered interpretations: instead of a quantum wave passing through both slits, we have a localized particle with nonlocal interactions with the other slit. Key to this explanation is dynamical nonlocality, which naturally appears in the Heisenberg picture as nonlocal equations of motion. This insight led us to develop an approach to quantum mechanics which relies on pre- and postselection, weak measurements, deterministic, and modular variables. We consider those properties of a single particle that are deterministic to be primal. The Heisenberg picture allows us to specify the most complete enumeration of such deterministic properties in contrast to the Schrödinger wave function, which remains an ensemble property. We exercise this approach by analyzing a version of the double-slit experiment augmented with postselection, showing that only it and not the wave function approach can be accommodated within a time-symmetric interpretation, where interference appears even when the particle is localized. Although the Heisenberg and Schrödinger pictures are equivalent formulations, nevertheless, the framework presented here has led to insights, intuitions, and experiments that were missed from the old perspective.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Deptuch, G. W.; Fahim, F.; Grybos, P.
An on-chip implementable algorithm for allocation of an X-ray photon imprint, called a hit, to a single pixel in the presence of charge sharing in a highly segmented pixel detector is described. Its proof-of-principle implementation is also given supported by the results of tests using a highly collimated X-ray photon beam from a synchrotron source. The algorithm handles asynchronous arrivals of X-ray photons. Activation of groups of pixels, comparisons of peak amplitudes of pulses within an active neighborhood and finally latching of the results of these comparisons constitute the three procedural steps of the algorithm. A grouping of pixels tomore » one virtual pixel that recovers composite signals and event driven strobes to control comparisons of fractional signals between neighboring pixels are the actuators of the algorithm. The circuitry necessary to implement the algorithm requires an extensive inter-pixel connection grid of analog and digital signals that are exchanged between pixels. A test-circuit implementation of the algorithm was achieved with a small array of 32×32 pixels and the device was exposed to an 8 keV highly collimated to a diameter of 3 μm X-ray beam. The results of these tests are given in the paper assessing physical implementation of the algorithm.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Deptuch, Grzegorz W.; Fahim, Farah; Grybos, Pawel
An on-chip implementable algorithm for allocation of an X-ray photon imprint, called a hit, to a single pixel in the presence of charge sharing in a highly segmented pixel detector is described. Its proof-of-principle implementation is also given supported by the results of tests using a highly collimated X-ray photon beam from a synchrotron source. The algorithm handles asynchronous arrivals of X-ray photons. Activation of groups of pixels, comparisons of peak amplitudes of pulses within an active neighborhood and finally latching of the results of these comparisons constitute the three procedural steps of the algorithm. A grouping of pixels tomore » one virtual pixel, that recovers composite signals and event driven strobes, to control comparisons of fractional signals between neighboring pixels are the actuators of the algorithm. The circuitry necessary to implement the algorithm requires an extensive inter-pixel connection grid of analog and digital signals, that are exchanged between pixels. A test-circuit implementation of the algorithm was achieved with a small array of 32 × 32 pixels and the device was exposed to an 8 keV highly collimated to a diameter of 3-μm X-ray beam. Furthermore, the results of these tests are given in this paper assessing physical implementation of the algorithm.« less
Rapid algorithm prototyping and implementation for power quality measurement
NASA Astrophysics Data System (ADS)
Kołek, Krzysztof; Piątek, Krzysztof
2015-12-01
This article presents a Model-Based Design (MBD) approach to rapidly implement power quality (PQ) metering algorithms. Power supply quality is a very important aspect of modern power systems and will become even more important in future smart grids. In this case, maintaining the PQ parameters at the desired level will require efficient implementation methods of the metering algorithms. Currently, the development of new, advanced PQ metering algorithms requires new hardware with adequate computational capability and time intensive, cost-ineffective manual implementations. An alternative, considered here, is an MBD approach. The MBD approach focuses on the modelling and validation of the model by simulation, which is well-supported by a Computer-Aided Engineering (CAE) packages. This paper presents two algorithms utilized in modern PQ meters: a phase-locked loop based on an Enhanced Phase Locked Loop (EPLL), and the flicker measurement according to the IEC 61000-4-15 standard. The algorithms were chosen because of their complexity and non-trivial development. They were first modelled in the MATLAB/Simulink package, then tested and validated in a simulation environment. The models, in the form of Simulink diagrams, were next used to automatically generate C code. The code was compiled and executed in real-time on the Zynq Xilinx platform that combines a reconfigurable Field Programmable Gate Array (FPGA) with a dual-core processor. The MBD development of PQ algorithms, automatic code generation, and compilation form a rapid algorithm prototyping and implementation path for PQ measurements. The main advantage of this approach is the ability to focus on the design, validation, and testing stages while skipping over implementation issues. The code generation process renders production-ready code that can be easily used on the target hardware. This is especially important when standards for PQ measurement are in constant development, and the PQ issues in emerging smart grids will require tools for rapid development and implementation of such algorithms.
Implementation of software-based sensor linearization algorithms on low-cost microcontrollers.
Erdem, Hamit
2010-10-01
Nonlinear sensors and microcontrollers are used in many embedded system designs. As the input-output characteristic of most sensors is nonlinear in nature, obtaining data from a nonlinear sensor by using an integer microcontroller has always been a design challenge. This paper discusses the implementation of six software-based sensor linearization algorithms for low-cost microcontrollers. The comparative study of the linearization algorithms is performed by using a nonlinear optical distance-measuring sensor. The performance of the algorithms is examined with respect to memory space usage, linearization accuracy and algorithm execution time. The implementation and comparison results can be used for selection of a linearization algorithm based on the sensor transfer function, expected linearization accuracy and microcontroller capacity. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.
Neural Generalized Predictive Control: A Newton-Raphson Implementation
NASA Technical Reports Server (NTRS)
Soloway, Donald; Haley, Pamela J.
1997-01-01
An efficient implementation of Generalized Predictive Control using a multi-layer feedforward neural network as the plant's nonlinear model is presented. In using Newton-Raphson as the optimization algorithm, the number of iterations needed for convergence is significantly reduced from other techniques. The main cost of the Newton-Raphson algorithm is in the calculation of the Hessian, but even with this overhead the low iteration numbers make Newton-Raphson faster than other techniques and a viable algorithm for real-time control. This paper presents a detailed derivation of the Neural Generalized Predictive Control algorithm with Newton-Raphson as the minimization algorithm. Simulation results show convergence to a good solution within two iterations and timing data show that real-time control is possible. Comments about the algorithm's implementation are also included.
Regier, Michael D; Moodie, Erica E M
2016-05-01
We propose an extension of the EM algorithm that exploits the common assumption of unique parameterization, corrects for biases due to missing data and measurement error, converges for the specified model when standard implementation of the EM algorithm has a low probability of convergence, and reduces a potentially complex algorithm into a sequence of smaller, simpler, self-contained EM algorithms. We use the theory surrounding the EM algorithm to derive the theoretical results of our proposal, showing that an optimal solution over the parameter space is obtained. A simulation study is used to explore the finite sample properties of the proposed extension when there is missing data and measurement error. We observe that partitioning the EM algorithm into simpler steps may provide better bias reduction in the estimation of model parameters. The ability to breakdown a complicated problem in to a series of simpler, more accessible problems will permit a broader implementation of the EM algorithm, permit the use of software packages that now implement and/or automate the EM algorithm, and make the EM algorithm more accessible to a wider and more general audience.
Overby, Casey Lynnette; Pathak, Jyotishman; Gottesman, Omri; Haerian, Krystl; Perotte, Adler; Murphy, Sean; Bruce, Kevin; Johnson, Stephanie; Talwalkar, Jayant; Shen, Yufeng; Ellis, Steve; Kullo, Iftikhar; Chute, Christopher; Friedman, Carol; Bottinger, Erwin; Hripcsak, George; Weng, Chunhua
2013-01-01
Objective To describe a collaborative approach for developing an electronic health record (EHR) phenotyping algorithm for drug-induced liver injury (DILI). Methods We analyzed types and causes of differences in DILI case definitions provided by two institutions—Columbia University and Mayo Clinic; harmonized two EHR phenotyping algorithms; and assessed the performance, measured by sensitivity, specificity, positive predictive value, and negative predictive value, of the resulting algorithm at three institutions except that sensitivity was measured only at Columbia University. Results Although these sites had the same case definition, their phenotyping methods differed by selection of liver injury diagnoses, inclusion of drugs cited in DILI cases, laboratory tests assessed, laboratory thresholds for liver injury, exclusion criteria, and approaches to validating phenotypes. We reached consensus on a DILI phenotyping algorithm and implemented it at three institutions. The algorithm was adapted locally to account for differences in populations and data access. Implementations collectively yielded 117 algorithm-selected cases and 23 confirmed true positive cases. Discussion Phenotyping for rare conditions benefits significantly from pooling data across institutions. Despite the heterogeneity of EHRs and varied algorithm implementations, we demonstrated the portability of this algorithm across three institutions. The performance of this algorithm for identifying DILI was comparable with other computerized approaches to identify adverse drug events. Conclusions Phenotyping algorithms developed for rare and complex conditions are likely to require adaptive implementation at multiple institutions. Better approaches are also needed to share algorithms. Early agreement on goals, data sources, and validation methods may improve the portability of the algorithms. PMID:23837993
Maximum-likelihood soft-decision decoding of block codes using the A* algorithm
NASA Technical Reports Server (NTRS)
Ekroot, L.; Dolinar, S.
1994-01-01
The A* algorithm finds the path in a finite depth binary tree that optimizes a function. Here, it is applied to maximum-likelihood soft-decision decoding of block codes where the function optimized over the codewords is the likelihood function of the received sequence given each codeword. The algorithm considers codewords one bit at a time, making use of the most reliable received symbols first and pursuing only the partially expanded codewords that might be maximally likely. A version of the A* algorithm for maximum-likelihood decoding of block codes has been implemented for block codes up to 64 bits in length. The efficiency of this algorithm makes simulations of codes up to length 64 feasible. This article details the implementation currently in use, compares the decoding complexity with that of exhaustive search and Viterbi decoding algorithms, and presents performance curves obtained with this implementation of the A* algorithm for several codes.
DOT National Transportation Integrated Search
2000-02-01
A Fuzzy Logic Ramp Metering Algorithm was implemented on 126 ramps in the greater Seattle area. This report documents the implementation of the Fuzzy Logic Ramp Metering Algorithm at the Northwest District of the Washington State Department of Transp...
Jamming protection of spread spectrum RFID system
NASA Astrophysics Data System (ADS)
Mazurek, Gustaw
2006-10-01
This paper presents a new transform-domain processing algorithm for rejection of narrowband interferences in RFID/DS-CDMA systems. The performance of the proposed algorithm has been verified via computer simulations. Implementation issues have been discussed. The algorithm can be implemented in the FPGA or DSP technology.
Operating Quantum States in Single Magnetic Molecules: Implementation of Grover's Quantum Algorithm.
Godfrin, C; Ferhat, A; Ballou, R; Klyatskaya, S; Ruben, M; Wernsdorfer, W; Balestro, F
2017-11-03
Quantum algorithms use the principles of quantum mechanics, such as, for example, quantum superposition, in order to solve particular problems outperforming standard computation. They are developed for cryptography, searching, optimization, simulation, and solving large systems of linear equations. Here, we implement Grover's quantum algorithm, proposed to find an element in an unsorted list, using a single nuclear 3/2 spin carried by a Tb ion sitting in a single molecular magnet transistor. The coherent manipulation of this multilevel quantum system (qudit) is achieved by means of electric fields only. Grover's search algorithm is implemented by constructing a quantum database via a multilevel Hadamard gate. The Grover sequence then allows us to select each state. The presented method is of universal character and can be implemented in any multilevel quantum system with nonequal spaced energy levels, opening the way to novel quantum search algorithms.
An acceleration framework for synthetic aperture radar algorithms
NASA Astrophysics Data System (ADS)
Kim, Youngsoo; Gloster, Clay S.; Alexander, Winser E.
2017-04-01
Algorithms for radar signal processing, such as Synthetic Aperture Radar (SAR) are computationally intensive and require considerable execution time on a general purpose processor. Reconfigurable logic can be used to off-load the primary computational kernel onto a custom computing machine in order to reduce execution time by an order of magnitude as compared to kernel execution on a general purpose processor. Specifically, Field Programmable Gate Arrays (FPGAs) can be used to accelerate these kernels using hardware-based custom logic implementations. In this paper, we demonstrate a framework for algorithm acceleration. We used SAR as a case study to illustrate the potential for algorithm acceleration offered by FPGAs. Initially, we profiled the SAR algorithm and implemented a homomorphic filter using a hardware implementation of the natural logarithm. Experimental results show a linear speedup by adding reasonably small processing elements in Field Programmable Gate Array (FPGA) as opposed to using a software implementation running on a typical general purpose processor.
Operating Quantum States in Single Magnetic Molecules: Implementation of Grover's Quantum Algorithm
NASA Astrophysics Data System (ADS)
Godfrin, C.; Ferhat, A.; Ballou, R.; Klyatskaya, S.; Ruben, M.; Wernsdorfer, W.; Balestro, F.
2017-11-01
Quantum algorithms use the principles of quantum mechanics, such as, for example, quantum superposition, in order to solve particular problems outperforming standard computation. They are developed for cryptography, searching, optimization, simulation, and solving large systems of linear equations. Here, we implement Grover's quantum algorithm, proposed to find an element in an unsorted list, using a single nuclear 3 /2 spin carried by a Tb ion sitting in a single molecular magnet transistor. The coherent manipulation of this multilevel quantum system (qudit) is achieved by means of electric fields only. Grover's search algorithm is implemented by constructing a quantum database via a multilevel Hadamard gate. The Grover sequence then allows us to select each state. The presented method is of universal character and can be implemented in any multilevel quantum system with nonequal spaced energy levels, opening the way to novel quantum search algorithms.
Algorithm implementation on the Navier-Stokes computer
DOE Office of Scientific and Technical Information (OSTI.GOV)
Krist, S.E.; Zang, T.A.
1987-03-01
The Navier-Stokes Computer is a multi-purpose parallel-processing supercomputer which is currently under development at Princeton University. It consists of multiple local memory parallel processors, called Nodes, which are interconnected in a hypercube network. Details of the procedures involved in implementing an algorithm on the Navier-Stokes computer are presented. The particular finite difference algorithm considered in this analysis was developed for simulation of laminar-turbulent transition in wall bounded shear flows. Projected timing results for implementing this algorithm indicate that operation rates in excess of 42 GFLOPS are feasible on a 128 Node machine.
Algorithm implementation on the Navier-Stokes computer
NASA Technical Reports Server (NTRS)
Krist, Steven E.; Zang, Thomas A.
1987-01-01
The Navier-Stokes Computer is a multi-purpose parallel-processing supercomputer which is currently under development at Princeton University. It consists of multiple local memory parallel processors, called Nodes, which are interconnected in a hypercube network. Details of the procedures involved in implementing an algorithm on the Navier-Stokes computer are presented. The particular finite difference algorithm considered in this analysis was developed for simulation of laminar-turbulent transition in wall bounded shear flows. Projected timing results for implementing this algorithm indicate that operation rates in excess of 42 GFLOPS are feasible on a 128 Node machine.
An implementation of the look-ahead Lanczos algorithm for non-Hermitian matrices, part 1
NASA Technical Reports Server (NTRS)
Freund, Roland W.; Gutknecht, Martin H.; Nachtigal, Noel M.
1990-01-01
The nonsymmetric Lanczos method can be used to compute eigenvalues of large sparse non-Hermitian matrices or to solve large sparse non-Hermitian linear systems. However, the original Lanczos algorithm is susceptible to possible breakdowns and potential instabilities. We present an implementation of a look-ahead version of the Lanczos algorithm which overcomes these problems by skipping over those steps in which a breakdown or near-breakdown would occur in the standard process. The proposed algorithm can handle look-ahead steps of any length and is not restricted to steps of length 2, as earlier implementations are. Also, our implementation has the feature that it requires roughly the same number of inner products as the standard Lanczos process without look-ahead.
A Discussion of Using a Reconfigurable Processor to Implement the Discrete Fourier Transform
NASA Technical Reports Server (NTRS)
White, Michael J.
2004-01-01
This paper presents the design and implementation of the Discrete Fourier Transform (DFT) algorithm on a reconfigurable processor system. While highly applicable to many engineering problems, the DFT is an extremely computationally intensive algorithm. Consequently, the eventual goal of this work is to enhance the execution of a floating-point precision DFT algorithm by off loading the algorithm from the computing system. This computing system, within the context of this research, is a typical high performance desktop computer with an may of field programmable gate arrays (FPGAs). FPGAs are hardware devices that are configured by software to execute an algorithm. If it is desired to change the algorithm, the software is changed to reflect the modification, then download to the FPGA, which is then itself modified. This paper will discuss methodology for developing the DFT algorithm to be implemented on the FPGA. We will discuss the algorithm, the FPGA code effort, and the results to date.
Efficient image compression algorithm for computer-animated images
NASA Astrophysics Data System (ADS)
Yfantis, Evangelos A.; Au, Matthew Y.; Miel, G.
1992-10-01
An image compression algorithm is described. The algorithm is an extension of the run-length image compression algorithm and its implementation is relatively easy. This algorithm was implemented and compared with other existing popular compression algorithms and with the Lempel-Ziv (LZ) coding. The Lempel-Ziv algorithm is available as a utility in the UNIX operating system and is also referred to as the UNIX uncompress. Sometimes our algorithm is best in terms of saving memory space, and sometimes one of the competing algorithms is best. The algorithm is lossless, and the intent is for the algorithm to be used in computer graphics animated images. Comparisons made with the LZ algorithm indicate that the decompression time using our algorithm is faster than that using the LZ algorithm. Once the data are in memory, a relatively simple and fast transformation is applied to uncompress the file.
de Paula, Lauro C. M.; Soares, Anderson S.; de Lima, Telma W.; Delbem, Alexandre C. B.; Coelho, Clarimar J.; Filho, Arlindo R. G.
2014-01-01
Several variable selection algorithms in multivariate calibration can be accelerated using Graphics Processing Units (GPU). Among these algorithms, the Firefly Algorithm (FA) is a recent proposed metaheuristic that may be used for variable selection. This paper presents a GPU-based FA (FA-MLR) with multiobjective formulation for variable selection in multivariate calibration problems and compares it with some traditional sequential algorithms in the literature. The advantage of the proposed implementation is demonstrated in an example involving a relatively large number of variables. The results showed that the FA-MLR, in comparison with the traditional algorithms is a more suitable choice and a relevant contribution for the variable selection problem. Additionally, the results also demonstrated that the FA-MLR performed in a GPU can be five times faster than its sequential implementation. PMID:25493625
de Paula, Lauro C M; Soares, Anderson S; de Lima, Telma W; Delbem, Alexandre C B; Coelho, Clarimar J; Filho, Arlindo R G
2014-01-01
Several variable selection algorithms in multivariate calibration can be accelerated using Graphics Processing Units (GPU). Among these algorithms, the Firefly Algorithm (FA) is a recent proposed metaheuristic that may be used for variable selection. This paper presents a GPU-based FA (FA-MLR) with multiobjective formulation for variable selection in multivariate calibration problems and compares it with some traditional sequential algorithms in the literature. The advantage of the proposed implementation is demonstrated in an example involving a relatively large number of variables. The results showed that the FA-MLR, in comparison with the traditional algorithms is a more suitable choice and a relevant contribution for the variable selection problem. Additionally, the results also demonstrated that the FA-MLR performed in a GPU can be five times faster than its sequential implementation.
Machine-checked proofs of the design and implementation of a fault-tolerant circuit
NASA Technical Reports Server (NTRS)
Bevier, William R.; Young, William D.
1990-01-01
A formally verified implementation of the 'oral messages' algorithm of Pease, Shostak, and Lamport is described. An abstract implementation of the algorithm is verified to achieve interactive consistency in the presence of faults. This abstract characterization is then mapped down to a hardware level implementation which inherits the fault-tolerant characteristics of the abstract version. All steps in the proof were checked with the Boyer-Moore theorem prover. A significant results is the demonstration of a fault-tolerant device that is formally specified and whose implementation is proved correct with respect to this specification. A significant simplifying assumption is that the redundant processors behave synchronously. A mechanically checked proof that the oral messages algorithm is 'optimal' in the sense that no algorithm which achieves agreement via similar message passing can tolerate a larger proportion of faulty processor is also described.
A Comparative Evaluation of Anomaly Detection Algorithms for Maritime Video Surveillance
2011-01-01
of k-means clustering and the k- NN Localized p-value Estimator ( KNN -LPE). K-means is a popular distance-based clustering algorithm while KNN -LPE...implemented the sparse cluster identification rule we described in Section 3.1. 2. k-NN Localized p-value Estimator ( KNN -LPE): We implemented this using...Average Density ( KNN -NAD): This was implemented as described in Section 3.4. Algorithm Parameter Settings The global and local density-based anomaly
NASA Astrophysics Data System (ADS)
Wu, Yuanfeng; Gao, Lianru; Zhang, Bing; Zhao, Haina; Li, Jun
2014-01-01
We present a parallel implementation of the optimized maximum noise fraction (G-OMNF) transform algorithm for feature extraction of hyperspectral images on commodity graphics processing units (GPUs). The proposed approach explored the algorithm data-level concurrency and optimized the computing flow. We first defined a three-dimensional grid, in which each thread calculates a sub-block data to easily facilitate the spatial and spectral neighborhood data searches in noise estimation, which is one of the most important steps involved in OMNF. Then, we optimized the processing flow and computed the noise covariance matrix before computing the image covariance matrix to reduce the original hyperspectral image data transmission. These optimization strategies can greatly improve the computing efficiency and can be applied to other feature extraction algorithms. The proposed parallel feature extraction algorithm was implemented on an Nvidia Tesla GPU using the compute unified device architecture and basic linear algebra subroutines library. Through the experiments on several real hyperspectral images, our GPU parallel implementation provides a significant speedup of the algorithm compared with the CPU implementation, especially for highly data parallelizable and arithmetically intensive algorithm parts, such as noise estimation. In order to further evaluate the effectiveness of G-OMNF, we used two different applications: spectral unmixing and classification for evaluation. Considering the sensor scanning rate and the data acquisition time, the proposed parallel implementation met the on-board real-time feature extraction.
AlgoRun: a Docker-based packaging system for platform-agnostic implemented algorithms.
Hosny, Abdelrahman; Vera-Licona, Paola; Laubenbacher, Reinhard; Favre, Thibauld
2016-08-01
There is a growing need in bioinformatics for easy-to-use software implementations of algorithms that are usable across platforms. At the same time, reproducibility of computational results is critical and often a challenge due to source code changes over time and dependencies. The approach introduced in this paper addresses both of these needs with AlgoRun, a dedicated packaging system for implemented algorithms, using Docker technology. Implemented algorithms, packaged with AlgoRun, can be executed through a user-friendly interface directly from a web browser or via a standardized RESTful web API to allow easy integration into more complex workflows. The packaged algorithm includes the entire software execution environment, thereby eliminating the common problem of software dependencies and the irreproducibility of computations over time. AlgoRun-packaged algorithms can be published on http://algorun.org, a centralized searchable directory to find existing AlgoRun-packaged algorithms. AlgoRun is available at http://algorun.org and the source code under GPL license is available at https://github.com/algorun laubenbacher@uchc.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Katouda, Michio; Naruse, Akira; Hirano, Yukihiko; Nakajima, Takahito
2016-11-15
A new parallel algorithm and its implementation for the RI-MP2 energy calculation utilizing peta-flop-class many-core supercomputers are presented. Some improvements from the previous algorithm (J. Chem. Theory Comput. 2013, 9, 5373) have been performed: (1) a dual-level hierarchical parallelization scheme that enables the use of more than 10,000 Message Passing Interface (MPI) processes and (2) a new data communication scheme that reduces network communication overhead. A multi-node and multi-GPU implementation of the present algorithm is presented for calculations on a central processing unit (CPU)/graphics processing unit (GPU) hybrid supercomputer. Benchmark results of the new algorithm and its implementation using the K computer (CPU clustering system) and TSUBAME 2.5 (CPU/GPU hybrid system) demonstrate high efficiency. The peak performance of 3.1 PFLOPS is attained using 80,199 nodes of the K computer. The peak performance of the multi-node and multi-GPU implementation is 514 TFLOPS using 1349 nodes and 4047 GPUs of TSUBAME 2.5. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
An implementation of the QMR method based on coupled two-term recurrences
NASA Technical Reports Server (NTRS)
Freund, Roland W.; Nachtigal, Noeel M.
1992-01-01
The authors have proposed a new Krylov subspace iteration, the quasi-minimal residual algorithm (QMR), for solving non-Hermitian linear systems. In the original implementation of the QMR method, the Lanczos process with look-ahead is used to generate basis vectors for the underlying Krylov subspaces. In the Lanczos algorithm, these basis vectors are computed by means of three-term recurrences. It has been observed that, in finite precision arithmetic, vector iterations based on three-term recursions are usually less robust than mathematically equivalent coupled two-term vector recurrences. This paper presents a look-ahead algorithm that constructs the Lanczos basis vectors by means of coupled two-term recursions. Implementation details are given, and the look-ahead strategy is described. A new implementation of the QMR method, based on this coupled two-term algorithm, is described. A simplified version of the QMR algorithm without look-ahead is also presented, and the special case of QMR for complex symmetric linear systems is considered. Results of numerical experiments comparing the original and the new implementations of the QMR method are reported.
Genetic algorithms using SISAL parallel programming language
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tejada, S.
1994-05-06
Genetic algorithms are a mathematical optimization technique developed by John Holland at the University of Michigan [1]. The SISAL programming language possesses many of the characteristics desired to implement genetic algorithms. SISAL is a deterministic, functional programming language which is inherently parallel. Because SISAL is functional and based on mathematical concepts, genetic algorithms can be efficiently translated into the language. Several of the steps involved in genetic algorithms, such as mutation, crossover, and fitness evaluation, can be parallelized using SISAL. In this paper I will l discuss the implementation and performance of parallel genetic algorithms in SISAL.
Efficient implementation of parallel three-dimensional FFT on clusters of PCs
NASA Astrophysics Data System (ADS)
Takahashi, Daisuke
2003-05-01
In this paper, we propose a high-performance parallel three-dimensional fast Fourier transform (FFT) algorithm on clusters of PCs. The three-dimensional FFT algorithm can be altered into a block three-dimensional FFT algorithm to reduce the number of cache misses. We show that the block three-dimensional FFT algorithm improves performance by utilizing the cache memory effectively. We use the block three-dimensional FFT algorithm to implement the parallel three-dimensional FFT algorithm. We succeeded in obtaining performance of over 1.3 GFLOPS on an 8-node dual Pentium III 1 GHz PC SMP cluster.
The Ghost of Electricity: A History of Electron Theory from 1897 to 1987.
ERIC Educational Resources Information Center
Adams, S. F.
1988-01-01
Discusses the history of electron theory from 1897 to 1987. Includes the works of some physicists, such as Thomson, Lorentz, De Broglie, Bohr, Pauli, Dirac, Feynman, Wheeler, Weinberg, and Salam. (YP)
Energies of Screened Coulomb Potentials.
ERIC Educational Resources Information Center
Lai, C. S.
1979-01-01
This article shows that, by applying the Hellman-Feynman theorem alone to screened Coulomb potentials, the first four coefficients in the energy series in powers of the perturbation parameter can be obtained from the unperturbed Coulomb system. (Author/HM)
NASA Astrophysics Data System (ADS)
Rosen, Charles; Siegel, Edward Carl-Ludwig; Feynman, Richard; Wunderman, Irwin; Smith, Adolph; Marinov, Vesco; Goldman, Jacob; Brine, Sergey; Poge, Larry; Schmidt, Erich; Young, Frederic; Goates-Bulmer, William-Steven; Lewis-Tsurakov-Altshuler, Thomas-Valerie-Genot; Ibm/Exxon Collaboration; Google/Uw Collaboration; Microsoft/Amazon Collaboration; Oracle/Sun Collaboration; Ostp/Dod/Dia/Nsa/W.-F./Boa/Ubs/Ub Collaboration
2013-03-01
Belew[Finding Out About, Cambridge(2000)] and separately full-decade pre-Page/Brin/Google FIRST Siegel-Rosen(Machine-Intelligence/Atherton)-Feynman-Smith-Marinov(Guzik Enterprises/Exxon-Enterprises/A.-I./Santa Clara)-Wunderman(H.-P.) [IBM Conf. on Computers and Mathematics, Stanford(1986); APS Mtgs.(1980s): Palo Alto/Santa Clara/San Francisco/...(1980s) MRS Spring-Mtgs.(1980s): Palo Alto/San Jose/San Francisco/...(1980-1992) FIRST quantum-computing via Bose-Einstein quantum-statistics(BEQS) Bose-Einstein CONDENSATION (BEC) in artificial-intelligence(A-I) artificial neural-networks(A-N-N) and biological neural-networks(B-N-N) and Siegel[J. Noncrystalline-Solids 40, 453(1980); Symp. on Fractals..., MRS Fall-Mtg., Boston(1989)-5-papers; Symp. on Scaling..., (1990); Symp. on Transport in Geometric-Constraint (1990)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Soltz, R. A.; Danagoulian, A.; Sheets, S.
Theoretical calculations indicate that the value of the Feynman variance, Y2F for the emitted distribution of neutrons from ssionable exhibits a strong monotonic de- pendence on a the multiplication, M, of a quantity of special nuclear material. In 2012 we performed a series of measurements at the Passport Inc. facility using a 9- MeV bremsstrahlung CW beam of photons incident on small quantities of uranium with liquid scintillator detectors. For the set of objects studies we observed deviations in the expected monotonic dependence, and these deviations were later con rmed by MCNP simulations. In this report, we modify the theorymore » to account for the contri- bution from the initial photo- ssion and benchmark the new theory with a series of MCNP simulations on DU, LEU, and HEU objects spanning a wide range of masses and multiplication values.« less
Tchouar, N; Ould-Kaddour, F; Levesque, D
2004-10-15
The properties of liquid methane, liquid neon, and gas helium are calculated at low temperatures over a large range of pressure from the classical molecular-dynamics simulations. The molecular interactions are represented by the Lennard-Jones pair potentials supplemented by quantum corrections following the Feynman-Hibbs approach. The equations of state, diffusion, and shear viscosity coefficients are determined for neon at 45 K, helium at 80 K, and methane at 110 K. A comparison is made with the existing experimental data and for thermodynamical quantities, with results computed from quantum numerical simulations when they are available. The theoretical variation of the viscosity coefficient with pressure is in good agreement with the experimental data when the quantum corrections are taken into account, thus reducing considerably the 60% discrepancy between the simulations and experiments in the absence of these corrections.
Sv-map between type I and heterotic sigma models
NASA Astrophysics Data System (ADS)
Fan, Wei; Fotopoulos, A.; Stieberger, S.; Taylor, T. R.
2018-05-01
The scattering amplitudes of gauge bosons in heterotic and open superstring theories are related by the single-valued projection which yields heterotic amplitudes by selecting a subset of multiple zeta value coefficients in the α‧ (string tension parameter) expansion of open string amplitudes. In the present work, we argue that this relation holds also at the level of low-energy expansions (or individual Feynman diagrams) of the respective effective actions, by investigating the beta functions of two-dimensional sigma models describing world-sheets of open and heterotic strings. We analyze the sigma model Feynman diagrams generating identical effective action terms in both theories and show that the heterotic coefficients are given by the single-valued projection of the open ones. The single-valued projection appears as a result of summing over all radial orderings of heterotic vertices on the complex plane representing string world-sheet.
Interference with electrons: from thought to real experiments
NASA Astrophysics Data System (ADS)
Matteucci, Giorgio
2013-11-01
The two-slit interference experiment is usually adopted to discuss the superposition principle applied to radiation and to show the peculiar wave behaviour of material particles. Diffraction and interference of electrons have been demonstrated using, as interferometry devices, a hole, a slit, double hole, two-slits, an electrostatic biprism etc. A number of books, short movies and lectures on the web try to popularize the mysterious behaviour of electrons on the basis of Feynman thought experiment which consists of a Young two-hole interferometer equipped with a detector to reveal single electrons. A short review is reported regarding, i) the pioneering attempts carried out to demonstrate that interference patterns could be obtained with single electrons through an interferometer and, ii) recent experiments, which can be considered as the realization of the thought electron interference experiments adopted by Einstein-Bohr and subsequently by Feynman to discuss key features of quantum physics.
Higher-order gravitational lensing reconstruction using Feynman diagrams
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jenkins, Elizabeth E.; Manohar, Aneesh V.; Yadav, Amit P.S.
2014-09-01
We develop a method for calculating the correlation structure of the Cosmic Microwave Background (CMB) using Feynman diagrams, when the CMB has been modified by gravitational lensing, Faraday rotation, patchy reionization, or other distorting effects. This method is used to calculate the bias of the Hu-Okamoto quadratic estimator in reconstructing the lensing power spectrum up to O (φ{sup 4}) in the lensing potential φ. We consider both the diagonal noise TT TT, EB EB, etc. and, for the first time, the off-diagonal noise TT TE, TB EB, etc. The previously noted large O (φ{sup 4}) term in the second order noise ismore » identified to come from a particular class of diagrams. It can be significantly reduced by a reorganization of the φ expansion. These improved estimators have almost no bias for the off-diagonal case involving only one B component of the CMB, such as EE EB.« less
Quantization of gauge fields, graph polynomials and graph homology
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kreimer, Dirk, E-mail: kreimer@physik.hu-berlin.de; Sars, Matthias; Suijlekom, Walter D. van
2013-09-15
We review quantization of gauge fields using algebraic properties of 3-regular graphs. We derive the Feynman integrand at n loops for a non-abelian gauge theory quantized in a covariant gauge from scalar integrands for connected 3-regular graphs, obtained from the two Symanzik polynomials. The transition to the full gauge theory amplitude is obtained by the use of a third, new, graph polynomial, the corolla polynomial. This implies effectively a covariant quantization without ghosts, where all the relevant signs of the ghost sector are incorporated in a double complex furnished by the corolla polynomial–we call it cycle homology–and by graph homology.more » -- Highlights: •We derive gauge theory Feynman from scalar field theory with 3-valent vertices. •We clarify the role of graph homology and cycle homology. •We use parametric renormalization and the new corolla polynomial.« less
NASA Astrophysics Data System (ADS)
Ma, Chao; Ma, Qinghua; Yao, Haixiang; Hou, Tiancheng
2018-03-01
In this paper, we propose to use the Fractional Stable Process (FSP) for option pricing. The FSP is one of the few candidates to directly model a number of desired empirical properties of asset price risk neutral dynamics. However, pricing the vanilla European option under FSP is difficult and problematic. In the paper, built upon the developed Feynman Path Integral inspired techniques, we present a novel computational model for option pricing, i.e. the Fractional Stable Process Path Integral (FSPPI) model under a general fractional stable distribution that tackles this problem. Numerical and empirical experiments show that the proposed pricing model provides a correction of the Black-Scholes pricing error - overpricing long term options, underpricing short term options; overpricing out-of-the-money options, underpricing in-the-money options without any additional structures such as stochastic volatility and a jump process.
NASA Astrophysics Data System (ADS)
Luna Acosta, German Aurelio
The masses of observed hadrons are fitted according to the kinematic predictions of Conformal Relativity. The hypothesis gives a remarkably good fit. The isospin SU(2) gauge invariant Lagrangian L(,(pi)NN)(x,(lamda)) is used in the calculation of d(sigma)/d(OMEGA) to 2nd-order Feynman graphs for simplified models of (pi)N(--->)(pi)N. The resulting infinite mass sums over the nucleon (Conformal) families are done via the Generalized-Sommerfeld-Watson Transform Theorem. Even though the models are too simple to be realistic, they indicate that if (DELTA)-internal lines were to be included, 2nd-order Feynman graphs may reproduce the experimental data qualitatively. The energy -dependence of the propagator and couplings in Conformal QFT is different from that of ordinary QFT. Suggestions for further work are made in the areas of ultra-violet divergences and OPEC calculations.
The Sustainable Technology Division has recently completed an implementation of the U.S. EPA's Waste Reduction (WAR) Algorithm that can be directly accessed from a Cape-Open compliant process modeling environment. The WAR Algorithm add-in can be used in AmsterChem's COFE (Cape-Op...
GPU implementation of prior image constrained compressed sensing (PICCS)
NASA Astrophysics Data System (ADS)
Nett, Brian E.; Tang, Jie; Chen, Guang-Hong
2010-04-01
The Prior Image Constrained Compressed Sensing (PICCS) algorithm (Med. Phys. 35, pg. 660, 2008) has been applied to several computed tomography applications with both standard CT systems and flat-panel based systems designed for guiding interventional procedures and radiation therapy treatment delivery. The PICCS algorithm typically utilizes a prior image which is reconstructed via the standard Filtered Backprojection (FBP) reconstruction algorithm. The algorithm then iteratively solves for the image volume that matches the measured data, while simultaneously assuring the image is similar to the prior image. The PICCS algorithm has demonstrated utility in several applications including: improved temporal resolution reconstruction, 4D respiratory phase specific reconstructions for radiation therapy, and cardiac reconstruction from data acquired on an interventional C-arm. One disadvantage of the PICCS algorithm, just as other iterative algorithms, is the long computation times typically associated with reconstruction. In order for an algorithm to gain clinical acceptance reconstruction must be achievable in minutes rather than hours. In this work the PICCS algorithm has been implemented on the GPU in order to significantly reduce the reconstruction time of the PICCS algorithm. The Compute Unified Device Architecture (CUDA) was used in this implementation.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Levi, Michele; Steinhoff, Jan, E-mail: michele.levi@upmc.fr, E-mail: jan.steinhoff@aei.mpg.de
2016-01-01
We implement the effective field theory for gravitating spinning objects in the post-Newtonian scheme at the next-to-next-to-leading order level to derive the gravitational spin-orbit interaction potential at the third and a half post-Newtonian order for rapidly rotating compact objects. From the next-to-next-to-leading order interaction potential, which we obtain here in a Lagrangian form for the first time, we derive straightforwardly the corresponding Hamiltonian. The spin-orbit sector constitutes the most elaborate spin dependent sector at each order, and accordingly we encounter a proliferation of the relevant Feynman diagrams, and a significant increase of the computational complexity. We present in detail themore » evaluation of the interaction potential, going over all contributing Feynman diagrams. The computation is carried out in terms of the ''nonrelativistic gravitational'' fields, which are advantageous also in spin dependent sectors, together with the various gauge choices included in the effective field theory for gravitating spinning objects, which also optimize the calculation. In addition, we automatize the effective field theory computations, and carry out the automated computations in parallel. Such automated effective field theory computations would be most useful to obtain higher order post-Newtonian corrections. We compare our Hamiltonian to the ADM Hamiltonian, and arrive at a complete agreement between the ADM and effective field theory results. Finally, we provide Hamiltonians in the center of mass frame, and complete gauge invariant relations among the binding energy, angular momentum, and orbital frequency of an inspiralling binary with generic compact spinning components to third and a half post-Newtonian order. The derivation presented here is essential to obtain further higher order post-Newtonian corrections, and to reach the accuracy level required for the successful detection of gravitational radiation.« less
Computationally efficient multibody simulations
NASA Technical Reports Server (NTRS)
Ramakrishnan, Jayant; Kumar, Manoj
1994-01-01
Computationally efficient approaches to the solution of the dynamics of multibody systems are presented in this work. The computational efficiency is derived from both the algorithmic and implementational standpoint. Order(n) approaches provide a new formulation of the equations of motion eliminating the assembly and numerical inversion of a system mass matrix as required by conventional algorithms. Computational efficiency is also gained in the implementation phase by the symbolic processing and parallel implementation of these equations. Comparison of this algorithm with existing multibody simulation programs illustrates the increased computational efficiency.
Implementation of Real-Time Feedback Flow Control Algorithms on a Canonical Testbed
NASA Technical Reports Server (NTRS)
Tian, Ye; Song, Qi; Cattafesta, Louis
2005-01-01
This report summarizes the activities on "Implementation of Real-Time Feedback Flow Control Algorithms on a Canonical Testbed." The work summarized consists primarily of two parts. The first part summarizes our previous work and the extensions to adaptive ID and control algorithms. The second part concentrates on the validation of adaptive algorithms by applying them to a vibration beam test bed. Extensions to flow control problems are discussed.
Implementation and evaluation of ILLIAC 4 algorithms for multispectral image processing
NASA Technical Reports Server (NTRS)
Swain, P. H.
1974-01-01
Data concerning a multidisciplinary and multi-organizational effort to implement multispectral data analysis algorithms on a revolutionary computer, the Illiac 4, are reported. The effectiveness and efficiency of implementing the digital multispectral data analysis techniques for producing useful land use classifications from satellite collected data were demonstrated.
NASA Technical Reports Server (NTRS)
Luke, Edward Allen
1993-01-01
Two algorithms capable of computing a transonic 3-D inviscid flow field about rotating machines are considered for parallel implementation. During the study of these algorithms, a significant new method of measuring the performance of parallel algorithms is developed. The theory that supports this new method creates an empirical definition of scalable parallel algorithms that is used to produce quantifiable evidence that a scalable parallel application was developed. The implementation of the parallel application and an automated domain decomposition tool are also discussed.
Automatic Data Distribution for CFD Applications on Structured Grids
NASA Technical Reports Server (NTRS)
Frumkin, Michael; Yan, Jerry
2000-01-01
Data distribution is an important step in implementation of any parallel algorithm. The data distribution determines data traffic, utilization of the interconnection network and affects the overall code efficiency. In recent years a number data distribution methods have been developed and used in real programs for improving data traffic. We use some of the methods for translating data dependence and affinity relations into data distribution directives. We describe an automatic data alignment and placement tool (ADAFT) which implements these methods and show it results for some CFD codes (NPB and ARC3D). Algorithms for program analysis and derivation of data distribution implemented in ADAFT are efficient three pass algorithms. Most algorithms have linear complexity with the exception of some graph algorithms having complexity O(n(sup 4)) in the worst case.
Automatic Data Distribution for CFD Applications on Structured Grids
NASA Technical Reports Server (NTRS)
Frumkin, Michael; Yan, Jerry
1999-01-01
Data distribution is an important step in implementation of any parallel algorithm. The data distribution determines data traffic, utilization of the interconnection network and affects the overall code efficiency. In recent years a number data distribution methods have been developed and used in real programs for improving data traffic. We use some of the methods for translating data dependence and affinity relations into data distribution directives. We describe an automatic data alignment and placement tool (ADAPT) which implements these methods and show it results for some CFD codes (NPB and ARC3D). Algorithms for program analysis and derivation of data distribution implemented in ADAPT are efficient three pass algorithms. Most algorithms have linear complexity with the exception of some graph algorithms having complexity O(n(sup 4)) in the worst case.
Low complexity 1D IDCT for 16-bit parallel architectures
NASA Astrophysics Data System (ADS)
Bivolarski, Lazar
2007-09-01
This paper shows that using the Loeffler, Ligtenberg, and Moschytz factorization of 8-point IDCT [2] one-dimensional (1-D) algorithm as a fast approximation of the Discrete Cosine Transform (DCT) and using only 16 bit numbers, it is possible to create in an IEEE 1180-1990 compliant and multiplierless algorithm with low computational complexity. This algorithm as characterized by its structure is efficiently implemented on parallel high performance architectures as well as due to its low complexity is sufficient for wide range of other architectures. Additional constraint on this work was the requirement of compliance with the existing MPEG standards. The hardware implementation complexity and low resources where also part of the design criteria for this algorithm. This implementation is also compliant with the precision requirements described in MPEG IDCT precision specification ISO/IEC 23002-1. Complexity analysis is performed as an extension to the simple measure of shifts and adds for the multiplierless algorithm as additional operations are included in the complexity measure to better describe the actual transform implementation complexity.
NASA Astrophysics Data System (ADS)
Genovese, Mariangela; Napoli, Ettore
2013-05-01
The identification of moving objects is a fundamental step in computer vision processing chains. The development of low cost and lightweight smart cameras steadily increases the request of efficient and high performance circuits able to process high definition video in real time. The paper proposes two processor cores aimed to perform the real time background identification on High Definition (HD, 1920 1080 pixel) video streams. The implemented algorithm is the OpenCV version of the Gaussian Mixture Model (GMM), an high performance probabilistic algorithm for the segmentation of the background that is however computationally intensive and impossible to implement on general purpose CPU with the constraint of real time processing. In the proposed paper, the equations of the OpenCV GMM algorithm are optimized in such a way that a lightweight and low power implementation of the algorithm is obtained. The reported performances are also the result of the use of state of the art truncated binary multipliers and ROM compression techniques for the implementation of the non-linear functions. The first circuit has commercial FPGA devices as a target and provides speed and logic resource occupation that overcome previously proposed implementations. The second circuit is oriented to an ASIC (UMC-90nm) standard cell implementation. Both implementations are able to process more than 60 frames per second in 1080p format, a frame rate compatible with HD television.
NASA Astrophysics Data System (ADS)
Lashkin, S. V.; Kozelkov, A. S.; Yalozo, A. V.; Gerasimov, V. Yu.; Zelensky, D. K.
2017-12-01
This paper describes the details of the parallel implementation of the SIMPLE algorithm for numerical solution of the Navier-Stokes system of equations on arbitrary unstructured grids. The iteration schemes for the serial and parallel versions of the SIMPLE algorithm are implemented. In the description of the parallel implementation, special attention is paid to computational data exchange among processors under the condition of the grid model decomposition using fictitious cells. We discuss the specific features for the storage of distributed matrices and implementation of vector-matrix operations in parallel mode. It is shown that the proposed way of matrix storage reduces the number of interprocessor exchanges. A series of numerical experiments illustrates the effect of the multigrid SLAE solver tuning on the general efficiency of the algorithm; the tuning involves the types of the cycles used (V, W, and F), the number of iterations of a smoothing operator, and the number of cells for coarsening. Two ways (direct and indirect) of efficiency evaluation for parallelization of the numerical algorithm are demonstrated. The paper presents the results of solving some internal and external flow problems with the evaluation of parallelization efficiency by two algorithms. It is shown that the proposed parallel implementation enables efficient computations for the problems on a thousand processors. Based on the results obtained, some general recommendations are made for the optimal tuning of the multigrid solver, as well as for selecting the optimal number of cells per processor.
Spiking neuron network Helmholtz machine.
Sountsov, Pavel; Miller, Paul
2015-01-01
An increasing amount of behavioral and neurophysiological data suggests that the brain performs optimal (or near-optimal) probabilistic inference and learning during perception and other tasks. Although many machine learning algorithms exist that perform inference and learning in an optimal way, the complete description of how one of those algorithms (or a novel algorithm) can be implemented in the brain is currently incomplete. There have been many proposed solutions that address how neurons can perform optimal inference but the question of how synaptic plasticity can implement optimal learning is rarely addressed. This paper aims to unify the two fields of probabilistic inference and synaptic plasticity by using a neuronal network of realistic model spiking neurons to implement a well-studied computational model called the Helmholtz Machine. The Helmholtz Machine is amenable to neural implementation as the algorithm it uses to learn its parameters, called the wake-sleep algorithm, uses a local delta learning rule. Our spiking-neuron network implements both the delta rule and a small example of a Helmholtz machine. This neuronal network can learn an internal model of continuous-valued training data sets without supervision. The network can also perform inference on the learned internal models. We show how various biophysical features of the neural implementation constrain the parameters of the wake-sleep algorithm, such as the duration of the wake and sleep phases of learning and the minimal sample duration. We examine the deviations from optimal performance and tie them to the properties of the synaptic plasticity rule.
Spiking neuron network Helmholtz machine
Sountsov, Pavel; Miller, Paul
2015-01-01
An increasing amount of behavioral and neurophysiological data suggests that the brain performs optimal (or near-optimal) probabilistic inference and learning during perception and other tasks. Although many machine learning algorithms exist that perform inference and learning in an optimal way, the complete description of how one of those algorithms (or a novel algorithm) can be implemented in the brain is currently incomplete. There have been many proposed solutions that address how neurons can perform optimal inference but the question of how synaptic plasticity can implement optimal learning is rarely addressed. This paper aims to unify the two fields of probabilistic inference and synaptic plasticity by using a neuronal network of realistic model spiking neurons to implement a well-studied computational model called the Helmholtz Machine. The Helmholtz Machine is amenable to neural implementation as the algorithm it uses to learn its parameters, called the wake-sleep algorithm, uses a local delta learning rule. Our spiking-neuron network implements both the delta rule and a small example of a Helmholtz machine. This neuronal network can learn an internal model of continuous-valued training data sets without supervision. The network can also perform inference on the learned internal models. We show how various biophysical features of the neural implementation constrain the parameters of the wake-sleep algorithm, such as the duration of the wake and sleep phases of learning and the minimal sample duration. We examine the deviations from optimal performance and tie them to the properties of the synaptic plasticity rule. PMID:25954191
The Even-Rho and Even-Epsilon Algorithms for Accelerating Convergence of a Numerical Sequence
1981-12-01
equal, leading to zero or very small divisors. Computer programs implementing these algorithms are given along with sample output. An appreciable amount...calculation of the array of Shank’s transforms or, -A equivalently, of the related Padd Table. The :other, the even-rho algorithm, is closely related...leading to zero or very small divisors. Computer pro- grams implementing these algorithms are given along with sample output. An appreciable amount or
Hybrid sparse blind deconvolution: an implementation of SOOT algorithm to real data
NASA Astrophysics Data System (ADS)
Pakmanesh, Parvaneh; Goudarzi, Alireza; Kourki, Meisam
2018-06-01
Getting information of seismic data depends on deconvolution as an important processing step; it provides the reflectivity series by signal compression. This compression can be obtained by removing the wavelet effects on the traces. The recently blind deconvolution has provided reliable performance for sparse signal recovery. In this study, two deconvolution methods have been implemented to the seismic data; the convolution of these methods provides a robust spiking deconvolution approach. This hybrid deconvolution is applied using the sparse deconvolution (MM algorithm) and the Smoothed-One-Over-Two algorithm (SOOT) in a chain. The MM algorithm is based on the minimization of the cost function defined by standards l1 and l2. After applying the two algorithms to the seismic data, the SOOT algorithm provided well-compressed data with a higher resolution than the MM algorithm. The SOOT algorithm requires initial values to be applied for real data, such as the wavelet coefficients and reflectivity series that can be achieved through the MM algorithm. The computational cost of the hybrid method is high, and it is necessary to be implemented on post-stack or pre-stack seismic data of complex structure regions.
A model-based 3D phase unwrapping algorithm using Gegenbauer polynomials.
Langley, Jason; Zhao, Qun
2009-09-07
The application of a two-dimensional (2D) phase unwrapping algorithm to a three-dimensional (3D) phase map may result in an unwrapped phase map that is discontinuous in the direction normal to the unwrapped plane. This work investigates the problem of phase unwrapping for 3D phase maps. The phase map is modeled as a product of three one-dimensional Gegenbauer polynomials. The orthogonality of Gegenbauer polynomials and their derivatives on the interval [-1, 1] are exploited to calculate the expansion coefficients. The algorithm was implemented using two well-known Gegenbauer polynomials: Chebyshev polynomials of the first kind and Legendre polynomials. Both implementations of the phase unwrapping algorithm were tested on 3D datasets acquired from a magnetic resonance imaging (MRI) scanner. The first dataset was acquired from a homogeneous spherical phantom. The second dataset was acquired using the same spherical phantom but magnetic field inhomogeneities were introduced by an external coil placed adjacent to the phantom, which provided an additional burden to the phase unwrapping algorithm. Then Gaussian noise was added to generate a low signal-to-noise ratio dataset. The third dataset was acquired from the brain of a human volunteer. The results showed that Chebyshev implementation and the Legendre implementation of the phase unwrapping algorithm give similar results on the 3D datasets. Both implementations of the phase unwrapping algorithm compare well to PRELUDE 3D, 3D phase unwrapping software well recognized for functional MRI.
NASA Astrophysics Data System (ADS)
Jin, Minglei; Jin, Weiqi; Li, Yiyang; Li, Shuo
2015-08-01
In this paper, we propose a novel scene-based non-uniformity correction algorithm for infrared image processing-temporal high-pass non-uniformity correction algorithm based on grayscale mapping (THP and GM). The main sources of non-uniformity are: (1) detector fabrication inaccuracies; (2) non-linearity and variations in the read-out electronics and (3) optical path effects. The non-uniformity will be reduced by non-uniformity correction (NUC) algorithms. The NUC algorithms are often divided into calibration-based non-uniformity correction (CBNUC) algorithms and scene-based non-uniformity correction (SBNUC) algorithms. As non-uniformity drifts temporally, CBNUC algorithms must be repeated by inserting a uniform radiation source which SBNUC algorithms do not need into the view, so the SBNUC algorithm becomes an essential part of infrared imaging system. The SBNUC algorithms' poor robustness often leads two defects: artifacts and over-correction, meanwhile due to complicated calculation process and large storage consumption, hardware implementation of the SBNUC algorithms is difficult, especially in Field Programmable Gate Array (FPGA) platform. The THP and GM algorithm proposed in this paper can eliminate the non-uniformity without causing defects. The hardware implementation of the algorithm only based on FPGA has two advantages: (1) low resources consumption, and (2) small hardware delay: less than 20 lines, it can be transplanted to a variety of infrared detectors equipped with FPGA image processing module, it can reduce the stripe non-uniformity and the ripple non-uniformity.
Sharp, G C; Kandasamy, N; Singh, H; Folkert, M
2007-10-07
This paper shows how to significantly accelerate cone-beam CT reconstruction and 3D deformable image registration using the stream-processing model. We describe data-parallel designs for the Feldkamp, Davis and Kress (FDK) reconstruction algorithm, and the demons deformable registration algorithm, suitable for use on a commodity graphics processing unit. The streaming versions of these algorithms are implemented using the Brook programming environment and executed on an NVidia 8800 GPU. Performance results using CT data of a preserved swine lung indicate that the GPU-based implementations of the FDK and demons algorithms achieve a substantial speedup--up to 80 times for FDK and 70 times for demons when compared to an optimized reference implementation on a 2.8 GHz Intel processor. In addition, the accuracy of the GPU-based implementations was found to be excellent. Compared with CPU-based implementations, the RMS differences were less than 0.1 Hounsfield unit for reconstruction and less than 0.1 mm for deformable registration.
Search Site submit Feynman Center for Innovation Los Alamos National Laboratory Collaboration for Explosives Detection Los Alamos National Laboratory Los Alamos Collaboration for Explosives Detection Menu is built upon Los Alamos' unparalleled explosive detection capabilities derived from the expertise of
1989-04-01
existing types of data compression methods amenable to our needs: Huffman, Arithmetic, BSTW, and Lempel - Ziv . The two algorithms with the most modest...APEX architecture. Recently we bega-, investigating various data compression algorithms with character- istics amenable to hardware implementation...This work has so far yielded a variant of the Lempel - Ziv algorithm that adapts continuously to its input and is appropriate to a hardware implementation
PACE: Power-Aware Computing Engines
2005-02-01
more costly than compu- tation on our test platform, and it is memory access that dominates most lossless data compression algorithms . In fact, even...Performance and implementation concerns A compression algorithm may be implemented with many different, yet reasonable, data structures (including...Related work This section discusses data compression for low- bandwidth devices and optimizing algorithms for low energy. Though much work has gone
DOE Office of Scientific and Technical Information (OSTI.GOV)
2010-09-30
The Umbra gbs (Graph-Based Search) library provides implementations of graph-based search/planning algorithms that can be applied to legacy graph data structures. Unlike some other graph algorithm libraries, this one does not require your graph class to inherit from a specific base class. Implementations of Dijkstra's Algorithm and A-Star search are included and can be used with graphs that are lazily-constructed.
NASA Technical Reports Server (NTRS)
Delaat, J. C.; Merrill, W. C.
1983-01-01
A sensor failure detection, isolation, and accommodation algorithm was developed which incorporates analytic sensor redundancy through software. This algorithm was implemented in a high level language on a microprocessor based controls computer. Parallel processing and state-of-the-art 16-bit microprocessors are used along with efficient programming practices to achieve real-time operation.
Molecular Monte Carlo Simulations Using Graphics Processing Units: To Waste Recycle or Not?
Kim, Jihan; Rodgers, Jocelyn M; Athènes, Manuel; Smit, Berend
2011-10-11
In the waste recycling Monte Carlo (WRMC) algorithm, (1) multiple trial states may be simultaneously generated and utilized during Monte Carlo moves to improve the statistical accuracy of the simulations, suggesting that such an algorithm may be well posed for implementation in parallel on graphics processing units (GPUs). In this paper, we implement two waste recycling Monte Carlo algorithms in CUDA (Compute Unified Device Architecture) using uniformly distributed random trial states and trial states based on displacement random-walk steps, and we test the methods on a methane-zeolite MFI framework system to evaluate their utility. We discuss the specific implementation details of the waste recycling GPU algorithm and compare the methods to other parallel algorithms optimized for the framework system. We analyze the relationship between the statistical accuracy of our simulations and the CUDA block size to determine the efficient allocation of the GPU hardware resources. We make comparisons between the GPU and the serial CPU Monte Carlo implementations to assess speedup over conventional microprocessors. Finally, we apply our optimized GPU algorithms to the important problem of determining free energy landscapes, in this case for molecular motion through the zeolite LTA.
Demonstration of a small programmable quantum computer with atomic qubits.
Debnath, S; Linke, N M; Figgatt, C; Landsman, K A; Wright, K; Monroe, C
2016-08-04
Quantum computers can solve certain problems more efficiently than any possible conventional computer. Small quantum algorithms have been demonstrated on multiple quantum computing platforms, many specifically tailored in hardware to implement a particular algorithm or execute a limited number of computational paths. Here we demonstrate a five-qubit trapped-ion quantum computer that can be programmed in software to implement arbitrary quantum algorithms by executing any sequence of universal quantum logic gates. We compile algorithms into a fully connected set of gate operations that are native to the hardware and have a mean fidelity of 98 per cent. Reconfiguring these gate sequences provides the flexibility to implement a variety of algorithms without altering the hardware. As examples, we implement the Deutsch-Jozsa and Bernstein-Vazirani algorithms with average success rates of 95 and 90 per cent, respectively. We also perform a coherent quantum Fourier transform on five trapped-ion qubits for phase estimation and period finding with average fidelities of 62 and 84 per cent, respectively. This small quantum computer can be scaled to larger numbers of qubits within a single register, and can be further expanded by connecting several such modules through ion shuttling or photonic quantum channels.
Demonstration of a small programmable quantum computer with atomic qubits
NASA Astrophysics Data System (ADS)
Debnath, S.; Linke, N. M.; Figgatt, C.; Landsman, K. A.; Wright, K.; Monroe, C.
2016-08-01
Quantum computers can solve certain problems more efficiently than any possible conventional computer. Small quantum algorithms have been demonstrated on multiple quantum computing platforms, many specifically tailored in hardware to implement a particular algorithm or execute a limited number of computational paths. Here we demonstrate a five-qubit trapped-ion quantum computer that can be programmed in software to implement arbitrary quantum algorithms by executing any sequence of universal quantum logic gates. We compile algorithms into a fully connected set of gate operations that are native to the hardware and have a mean fidelity of 98 per cent. Reconfiguring these gate sequences provides the flexibility to implement a variety of algorithms without altering the hardware. As examples, we implement the Deutsch-Jozsa and Bernstein-Vazirani algorithms with average success rates of 95 and 90 per cent, respectively. We also perform a coherent quantum Fourier transform on five trapped-ion qubits for phase estimation and period finding with average fidelities of 62 and 84 per cent, respectively. This small quantum computer can be scaled to larger numbers of qubits within a single register, and can be further expanded by connecting several such modules through ion shuttling or photonic quantum channels.
NASA Astrophysics Data System (ADS)
Gimazov, R.; Shidlovskiy, S.
2018-05-01
In this paper, we consider the architecture of the algorithm for extreme regulation in the photovoltaic system. An algorithm based on an adaptive neural network with fuzzy inference is proposed. The implementation of such an algorithm not only allows solving a number of problems in existing algorithms for extreme power regulation of photovoltaic systems, but also creates a reserve for the creation of a universal control system for a photovoltaic system.
NASA Technical Reports Server (NTRS)
Merrill, W. C.; Delaat, J. C.
1986-01-01
An advanced sensor failure detection, isolation, and accommodation (ADIA) algorithm has been developed for use with an aircraft turbofan engine control system. In a previous paper the authors described the ADIA algorithm and its real-time implementation. Subsequent improvements made to the algorithm and implementation are discussed, and the results of an evaluation presented. The evaluation used a real-time, hybrid computer simulation of an F100 turbofan engine.
Phase retrieval algorithm for JWST Flight and Testbed Telescope
NASA Astrophysics Data System (ADS)
Dean, Bruce H.; Aronstein, David L.; Smith, J. Scott; Shiri, Ron; Acton, D. Scott
2006-06-01
An image-based wavefront sensing and control algorithm for the James Webb Space Telescope (JWST) is presented. The algorithm heritage is discussed in addition to implications for algorithm performance dictated by NASA's Technology Readiness Level (TRL) 6. The algorithm uses feedback through an adaptive diversity function to avoid the need for phase-unwrapping post-processing steps. Algorithm results are demonstrated using JWST Testbed Telescope (TBT) commissioning data and the accuracy is assessed by comparison with interferometer results on a multi-wave phase aberration. Strategies for minimizing aliasing artifacts in the recovered phase are presented and orthogonal basis functions are implemented for representing wavefronts in irregular hexagonal apertures. Algorithm implementation on a parallel cluster of high-speed digital signal processors (DSPs) is also discussed.
NASA Astrophysics Data System (ADS)
Budiman, M. A.; Rachmawati, D.; Parlindungan, M. R.
2018-03-01
MDTM is a classical symmetric cryptographic algorithm. As with other classical algorithms, the MDTM Cipher algorithm is easy to implement but it is less secure compared to modern symmetric algorithms. In order to make it more secure, a stream cipher RC4A is added and thus the cryptosystem becomes super encryption. In this process, plaintexts derived from PDFs are firstly encrypted with the MDTM Cipher algorithm and are encrypted once more with the RC4A algorithm. The test results show that the value of complexity is Θ(n2) and the running time is linearly directly proportional to the length of plaintext characters and the keys entered.
[GNU Pattern: open source pattern hunter for biological sequences based on SPLASH algorithm].
Xu, Ying; Li, Yi-xue; Kong, Xiang-yin
2005-06-01
To construct a high performance open source software engine based on IBM SPLASH algorithm for later research on pattern discovery. Gpat, which is based on SPLASH algorithm, was developed by using open source software. GNU Pattern (Gpat) software was developped, which efficiently implemented the core part of SPLASH algorithm. Full source code of Gpat was also available for other researchers to modify the program under the GNU license. Gpat is a successful implementation of SPLASH algorithm and can be used as a basic framework for later research on pattern recognition in biological sequences.
GPU-based Branchless Distance-Driven Projection and Backprojection
Liu, Rui; Fu, Lin; De Man, Bruno; Yu, Hengyong
2017-01-01
Projection and backprojection operations are essential in a variety of image reconstruction and physical correction algorithms in CT. The distance-driven (DD) projection and backprojection are widely used for their highly sequential memory access pattern and low arithmetic cost. However, a typical DD implementation has an inner loop that adjusts the calculation depending on the relative position between voxel and detector cell boundaries. The irregularity of the branch behavior makes it inefficient to be implemented on massively parallel computing devices such as graphics processing units (GPUs). Such irregular branch behaviors can be eliminated by factorizing the DD operation as three branchless steps: integration, linear interpolation, and differentiation, all of which are highly amenable to massive vectorization. In this paper, we implement and evaluate a highly parallel branchless DD algorithm for 3D cone beam CT. The algorithm utilizes the texture memory and hardware interpolation on GPUs to achieve fast computational speed. The developed branchless DD algorithm achieved 137-fold speedup for forward projection and 188-fold speedup for backprojection relative to a single-thread CPU implementation. Compared with a state-of-the-art 32-thread CPU implementation, the proposed branchless DD achieved 8-fold acceleration for forward projection and 10-fold acceleration for backprojection. GPU based branchless DD method was evaluated by iterative reconstruction algorithms with both simulation and real datasets. It obtained visually identical images as the CPU reference algorithm. PMID:29333480
GPU-based Branchless Distance-Driven Projection and Backprojection.
Liu, Rui; Fu, Lin; De Man, Bruno; Yu, Hengyong
2017-12-01
Projection and backprojection operations are essential in a variety of image reconstruction and physical correction algorithms in CT. The distance-driven (DD) projection and backprojection are widely used for their highly sequential memory access pattern and low arithmetic cost. However, a typical DD implementation has an inner loop that adjusts the calculation depending on the relative position between voxel and detector cell boundaries. The irregularity of the branch behavior makes it inefficient to be implemented on massively parallel computing devices such as graphics processing units (GPUs). Such irregular branch behaviors can be eliminated by factorizing the DD operation as three branchless steps: integration, linear interpolation, and differentiation, all of which are highly amenable to massive vectorization. In this paper, we implement and evaluate a highly parallel branchless DD algorithm for 3D cone beam CT. The algorithm utilizes the texture memory and hardware interpolation on GPUs to achieve fast computational speed. The developed branchless DD algorithm achieved 137-fold speedup for forward projection and 188-fold speedup for backprojection relative to a single-thread CPU implementation. Compared with a state-of-the-art 32-thread CPU implementation, the proposed branchless DD achieved 8-fold acceleration for forward projection and 10-fold acceleration for backprojection. GPU based branchless DD method was evaluated by iterative reconstruction algorithms with both simulation and real datasets. It obtained visually identical images as the CPU reference algorithm.
NASA Astrophysics Data System (ADS)
Nguyen, An Hung; Guillemette, Thomas; Lambert, Andrew J.; Pickering, Mark R.; Garratt, Matthew A.
2017-09-01
Image registration is a fundamental image processing technique. It is used to spatially align two or more images that have been captured at different times, from different sensors, or from different viewpoints. There have been many algorithms proposed for this task. The most common of these being the well-known Lucas-Kanade (LK) and Horn-Schunck approaches. However, the main limitation of these approaches is the computational complexity required to implement the large number of iterations necessary for successful alignment of the images. Previously, a multi-pass image interpolation algorithm (MP-I2A) was developed to considerably reduce the number of iterations required for successful registration compared with the LK algorithm. This paper develops a kernel-warping algorithm (KWA), a modified version of the MP-I2A, which requires fewer iterations to successfully register two images and less memory space for the field-programmable gate array (FPGA) implementation than the MP-I2A. These reductions increase feasibility of the implementation of the proposed algorithm on FPGAs with very limited memory space and other hardware resources. A two-FPGA system rather than single FPGA system is successfully developed to implement the KWA in order to compensate insufficiency of hardware resources supported by one FPGA, and increase parallel processing ability and scalability of the system.
Software algorithm and hardware design for real-time implementation of new spectral estimator
2014-01-01
Background Real-time spectral analyzers can be difficult to implement for PC computer-based systems because of the potential for high computational cost, and algorithm complexity. In this work a new spectral estimator (NSE) is developed for real-time analysis, and compared with the discrete Fourier transform (DFT). Method Clinical data in the form of 216 fractionated atrial electrogram sequences were used as inputs. The sample rate for acquisition was 977 Hz, or approximately 1 millisecond between digital samples. Real-time NSE power spectra were generated for 16,384 consecutive data points. The same data sequences were used for spectral calculation using a radix-2 implementation of the DFT. The NSE algorithm was also developed for implementation as a real-time spectral analyzer electronic circuit board. Results The average interval for a single real-time spectral calculation in software was 3.29 μs for NSE versus 504.5 μs for DFT. Thus for real-time spectral analysis, the NSE algorithm is approximately 150× faster than the DFT. Over a 1 millisecond sampling period, the NSE algorithm had the capability to spectrally analyze a maximum of 303 data channels, while the DFT algorithm could only analyze a single channel. Moreover, for the 8 second sequences, the NSE spectral resolution in the 3-12 Hz range was 0.037 Hz while the DFT spectral resolution was only 0.122 Hz. The NSE was also found to be implementable as a standalone spectral analyzer board using approximately 26 integrated circuits at a cost of approximately $500. The software files used for analysis are included as a supplement, please see the Additional files 1 and 2. Conclusions The NSE real-time algorithm has low computational cost and complexity, and is implementable in both software and hardware for 1 millisecond updates of multichannel spectra. The algorithm may be helpful to guide radiofrequency catheter ablation in real time. PMID:24886214
Xiao, Kai; Chen, Danny Z; Hu, X Sharon; Zhou, Bo
2012-12-01
The three-dimensional digital differential analyzer (3D-DDA) algorithm is a widely used ray traversal method, which is also at the core of many convolution∕superposition (C∕S) dose calculation approaches. However, porting existing C∕S dose calculation methods onto graphics processing unit (GPU) has brought challenges to retaining the efficiency of this algorithm. In particular, straightforward implementation of the original 3D-DDA algorithm inflicts a lot of branch divergence which conflicts with the GPU programming model and leads to suboptimal performance. In this paper, an efficient GPU implementation of the 3D-DDA algorithm is proposed, which effectively reduces such branch divergence and improves performance of the C∕S dose calculation programs running on GPU. The main idea of the proposed method is to convert a number of conditional statements in the original 3D-DDA algorithm into a set of simple operations (e.g., arithmetic, comparison, and logic) which are better supported by the GPU architecture. To verify and demonstrate the performance improvement, this ray traversal method was integrated into a GPU-based collapsed cone convolution∕superposition (CCCS) dose calculation program. The proposed method has been tested using a water phantom and various clinical cases on an NVIDIA GTX570 GPU. The CCCS dose calculation program based on the efficient 3D-DDA ray traversal implementation runs 1.42 ∼ 2.67× faster than the one based on the original 3D-DDA implementation, without losing any accuracy. The results show that the proposed method can effectively reduce branch divergence in the original 3D-DDA ray traversal algorithm and improve the performance of the CCCS program running on GPU. Considering the wide utilization of the 3D-DDA algorithm, various applications can benefit from this implementation method.
EV Charging Algorithm Implementation with User Price Preference
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Bin; Hu, Boyang; Qiu, Charlie
2015-02-17
in this paper, we propose and implement a smart Electric Vehicle (EV) charging algorithm to control the EV charging infrastructures according to users’ price preferences. EVSE (Electric Vehicle Supply Equipment), equipped with bidirectional communication devices and smart meters, can be remotely monitored by the proposed charging algorithm applied to EV control center and mobile app. On the server side, ARIMA model is utilized to fit historical charging load data and perform day-ahead prediction. A pricing strategy with energy bidding policy is proposed and implemented to generate a charging price list to be broadcasted to EV users through mobile app. Onmore » the user side, EV drivers can submit their price preferences and daily travel schedules to negotiate with Control Center to consume the expected energy and minimize charging cost simultaneously. The proposed algorithm is tested and validated through the experimental implementations in UCLA parking lots.« less
General purpose graphic processing unit implementation of adaptive pulse compression algorithms
NASA Astrophysics Data System (ADS)
Cai, Jingxiao; Zhang, Yan
2017-07-01
This study introduces a practical approach to implement real-time signal processing algorithms for general surveillance radar based on NVIDIA graphical processing units (GPUs). The pulse compression algorithms are implemented using compute unified device architecture (CUDA) libraries such as CUDA basic linear algebra subroutines and CUDA fast Fourier transform library, which are adopted from open source libraries and optimized for the NVIDIA GPUs. For more advanced, adaptive processing algorithms such as adaptive pulse compression, customized kernel optimization is needed and investigated. A statistical optimization approach is developed for this purpose without needing much knowledge of the physical configurations of the kernels. It was found that the kernel optimization approach can significantly improve the performance. Benchmark performance is compared with the CPU performance in terms of processing accelerations. The proposed implementation framework can be used in various radar systems including ground-based phased array radar, airborne sense and avoid radar, and aerospace surveillance radar.
What does fault tolerant Deep Learning need from MPI?
DOE Office of Scientific and Technical Information (OSTI.GOV)
Amatya, Vinay C.; Vishnu, Abhinav; Siegel, Charles M.
Deep Learning (DL) algorithms have become the {\\em de facto} Machine Learning (ML) algorithm for large scale data analysis. DL algorithms are computationally expensive -- even distributed DL implementations which use MPI require days of training (model learning) time on commonly studied datasets. Long running DL applications become susceptible to faults -- requiring development of a fault tolerant system infrastructure, in addition to fault tolerant DL algorithms. This raises an important question: {\\em What is needed from MPI for designing fault tolerant DL implementations?} In this paper, we address this problem for permanent faults. We motivate the need for amore » fault tolerant MPI specification by an in-depth consideration of recent innovations in DL algorithms and their properties, which drive the need for specific fault tolerance features. We present an in-depth discussion on the suitability of different parallelism types (model, data and hybrid); a need (or lack thereof) for check-pointing of any critical data structures; and most importantly, consideration for several fault tolerance proposals (user-level fault mitigation (ULFM), Reinit) in MPI and their applicability to fault tolerant DL implementations. We leverage a distributed memory implementation of Caffe, currently available under the Machine Learning Toolkit for Extreme Scale (MaTEx). We implement our approaches by extending MaTEx-Caffe for using ULFM-based implementation. Our evaluation using the ImageNet dataset and AlexNet neural network topology demonstrates the effectiveness of the proposed fault tolerant DL implementation using OpenMPI based ULFM.« less
Maximum-Likelihood Estimation With a Contracting-Grid Search Algorithm
Hesterman, Jacob Y.; Caucci, Luca; Kupinski, Matthew A.; Barrett, Harrison H.; Furenlid, Lars R.
2010-01-01
A fast search algorithm capable of operating in multi-dimensional spaces is introduced. As a sample application, we demonstrate its utility in the 2D and 3D maximum-likelihood position-estimation problem that arises in the processing of PMT signals to derive interaction locations in compact gamma cameras. We demonstrate that the algorithm can be parallelized in pipelines, and thereby efficiently implemented in specialized hardware, such as field-programmable gate arrays (FPGAs). A 2D implementation of the algorithm is achieved in Cell/BE processors, resulting in processing speeds above one million events per second, which is a 20× increase in speed over a conventional desktop machine. Graphics processing units (GPUs) are used for a 3D application of the algorithm, resulting in processing speeds of nearly 250,000 events per second which is a 250× increase in speed over a conventional desktop machine. These implementations indicate the viability of the algorithm for use in real-time imaging applications. PMID:20824155
NASA Astrophysics Data System (ADS)
Gilbert, B. K.; Robb, R. A.; Chu, A.; Kenue, S. K.; Lent, A. H.; Swartzlander, E. E., Jr.
1981-02-01
Rapid advances during the past ten years of several forms of computer-assisted tomography (CT) have resulted in the development of numerous algorithms to convert raw projection data into cross-sectional images. These reconstruction algorithms are either 'iterative,' in which a large matrix algebraic equation is solved by successive approximation techniques; or 'closed form'. Continuing evolution of the closed form algorithms has allowed the newest versions to produce excellent reconstructed images in most applications. This paper will review several computer software and special-purpose digital hardware implementations of closed form algorithms, either proposed during the past several years by a number of workers or actually implemented in commercial or research CT scanners. The discussion will also cover a number of recently investigated algorithmic modifications which reduce the amount of computation required to execute the reconstruction process, as well as several new special-purpose digital hardware implementations under development in laboratories at the Mayo Clinic.
FPGA based charge acquisition algorithm for soft x-ray diagnostics system
NASA Astrophysics Data System (ADS)
Wojenski, A.; Kasprowicz, G.; Pozniak, K. T.; Zabolotny, W.; Byszuk, A.; Juszczyk, B.; Kolasinski, P.; Krawczyk, R. D.; Zienkiewicz, P.; Chernyshova, M.; Czarski, T.
2015-09-01
Soft X-ray (SXR) measurement systems working in tokamaks or with laser generated plasma can expect high photon fluxes. Therefore it is necessary to focus on data processing algorithms to have the best possible efficiency in term of processed photon events per second. This paper refers to recently designed algorithm and data-flow for implementation of charge data acquisition in FPGA. The algorithms are currently on implementation stage for the soft X-ray diagnostics system. In this paper despite of the charge processing algorithm is also described general firmware overview, data storage methods and other key components of the measurement system. The simulation section presents algorithm performance and expected maximum photon rate.
NASA Astrophysics Data System (ADS)
Mao, Heng; Wang, Xiao; Zhao, Dazun
2009-05-01
As a wavefront sensing (WFS) tool, Baseline algorithm, which is classified as the iterative-transform algorithm of phase retrieval, estimates the phase distribution at pupil from some known PSFs at defocus planes. By using multiple phase diversities and appropriate phase unwrapping methods, this algorithm can accomplish reliable unique solution and high dynamic phase measurement. In the paper, a Baseline algorithm based wavefront sensing experiment with modification of phase unwrapping has been implemented, and corresponding Graphical User Interfaces (GUI) software has also been given. The adaptability and repeatability of Baseline algorithm have been validated in experiments. Moreover, referring to the ZYGO interferometric results, the WFS accuracy of this algorithm has been exactly calibrated.
A Demons algorithm for image registration with locally adaptive regularization.
Cahill, Nathan D; Noble, J Alison; Hawkes, David J
2009-01-01
Thirion's Demons is a popular algorithm for nonrigid image registration because of its linear computational complexity and ease of implementation. It approximately solves the diffusion registration problem by successively estimating force vectors that drive the deformation toward alignment and smoothing the force vectors by Gaussian convolution. In this article, we show how the Demons algorithm can be generalized to allow image-driven locally adaptive regularization in a manner that preserves both the linear complexity and ease of implementation of the original Demons algorithm. We show that the proposed algorithm exhibits lower target registration error and requires less computational effort than the original Demons algorithm on the registration of serial chest CT scans of patients with lung nodules.
Use of the Hotelling observer to optimize image reconstruction in digital breast tomosynthesis
Sánchez, Adrian A.; Sidky, Emil Y.; Pan, Xiaochuan
2015-01-01
Abstract. We propose an implementation of the Hotelling observer that can be applied to the optimization of linear image reconstruction algorithms in digital breast tomosynthesis. The method is based on considering information within a specific region of interest, and it is applied to the optimization of algorithms for detectability of microcalcifications. Several linear algorithms are considered: simple back-projection, filtered back-projection, back-projection filtration, and Λ-tomography. The optimized algorithms are then evaluated through the reconstruction of phantom data. The method appears robust across algorithms and parameters and leads to the generation of algorithm implementations which subjectively appear optimized for the task of interest. PMID:26702408
Eroglu, Duygu Yilmaz; Ozmutlu, H Cenk
2014-01-01
We developed mixed integer programming (MIP) models and hybrid genetic-local search algorithms for the scheduling problem of unrelated parallel machines with job sequence and machine-dependent setup times and with job splitting property. The first contribution of this paper is to introduce novel algorithms which make splitting and scheduling simultaneously with variable number of subjobs. We proposed simple chromosome structure which is constituted by random key numbers in hybrid genetic-local search algorithm (GAspLA). Random key numbers are used frequently in genetic algorithms, but it creates additional difficulty when hybrid factors in local search are implemented. We developed algorithms that satisfy the adaptation of results of local search into the genetic algorithms with minimum relocation operation of genes' random key numbers. This is the second contribution of the paper. The third contribution of this paper is three developed new MIP models which are making splitting and scheduling simultaneously. The fourth contribution of this paper is implementation of the GAspLAMIP. This implementation let us verify the optimality of GAspLA for the studied combinations. The proposed methods are tested on a set of problems taken from the literature and the results validate the effectiveness of the proposed algorithms.
A distributed-memory approximation algorithm for maximum weight perfect bipartite matching
DOE Office of Scientific and Technical Information (OSTI.GOV)
Azad, Ariful; Buluc, Aydin; Li, Xiaoye S.
We design and implement an efficient parallel approximation algorithm for the problem of maximum weight perfect matching in bipartite graphs, i.e. the problem of finding a set of non-adjacent edges that covers all vertices and has maximum weight. This problem differs from the maximum weight matching problem, for which scalable approximation algorithms are known. It is primarily motivated by finding good pivots in scalable sparse direct solvers before factorization where sequential implementations of maximum weight perfect matching algorithms, such as those available in MC64, are widely used due to the lack of scalable alternatives. To overcome this limitation, we proposemore » a fully parallel distributed memory algorithm that first generates a perfect matching and then searches for weightaugmenting cycles of length four in parallel and iteratively augments the matching with a vertex disjoint set of such cycles. For most practical problems the weights of the perfect matchings generated by our algorithm are very close to the optimum. An efficient implementation of the algorithm scales up to 256 nodes (17,408 cores) on a Cray XC40 supercomputer and can solve instances that are too large to be handled by a single node using the sequential algorithm.« less
NASA Astrophysics Data System (ADS)
Alloul, Adam; Christensen, Neil D.; Degrande, Céline; Duhr, Claude; Fuks, Benjamin
2014-06-01
The program FEYNRULES is a MATHEMATICA package developed to facilitate the implementation of new physics theories into high-energy physics tools. Starting from a minimal set of information such as the model gauge symmetries, its particle content, parameters and Lagrangian, FEYNRULES provides all necessary routines to extract automatically from the Lagrangian (that can also be computed semi-automatically for supersymmetric theories) the associated Feynman rules. These can be further exported to several Monte Carlo event generators through dedicated interfaces, as well as translated into a PYTHON library, under the so-called UFO model format, agnostic of the model complexity, especially in terms of Lorentz and/or color structures appearing in the vertices or of number of external legs. In this work, we briefly report on the most recent new features that have been added to FEYNRULES, including full support for spin-1 fermions, a new module allowing for the automated diagonalization of the particle spectrum and a new set of routines dedicated to decay width calculations.
Mechanical Autonomous Stochastic Heat Engine
NASA Astrophysics Data System (ADS)
Serra-Garcia, Marc; Foehr, André; Molerón, Miguel; Lydon, Joseph; Chong, Christopher; Daraio, Chiara
2016-07-01
Stochastic heat engines are devices that generate work from random thermal motion using a small number of highly fluctuating degrees of freedom. Proposals for such devices have existed for more than a century and include the Maxwell demon and the Feynman ratchet. Only recently have they been demonstrated experimentally, using, e.g., thermal cycles implemented in optical traps. However, recent experimental demonstrations of classical stochastic heat engines are nonautonomous, since they require an external control system that prescribes a heating and cooling cycle and consume more energy than they produce. We present a heat engine consisting of three coupled mechanical resonators (two ribbons and a cantilever) subject to a stochastic drive. The engine uses geometric nonlinearities in the resonating ribbons to autonomously convert a random excitation into a low-entropy, nonpassive oscillation of the cantilever. The engine presents the anomalous heat transport property of negative thermal conductivity, consisting in the ability to passively transfer energy from a cold reservoir to a hot reservoir.
Mechanical Autonomous Stochastic Heat Engine.
Serra-Garcia, Marc; Foehr, André; Molerón, Miguel; Lydon, Joseph; Chong, Christopher; Daraio, Chiara
2016-07-01
Stochastic heat engines are devices that generate work from random thermal motion using a small number of highly fluctuating degrees of freedom. Proposals for such devices have existed for more than a century and include the Maxwell demon and the Feynman ratchet. Only recently have they been demonstrated experimentally, using, e.g., thermal cycles implemented in optical traps. However, recent experimental demonstrations of classical stochastic heat engines are nonautonomous, since they require an external control system that prescribes a heating and cooling cycle and consume more energy than they produce. We present a heat engine consisting of three coupled mechanical resonators (two ribbons and a cantilever) subject to a stochastic drive. The engine uses geometric nonlinearities in the resonating ribbons to autonomously convert a random excitation into a low-entropy, nonpassive oscillation of the cantilever. The engine presents the anomalous heat transport property of negative thermal conductivity, consisting in the ability to passively transfer energy from a cold reservoir to a hot reservoir.
RECOLA2: REcursive Computation of One-Loop Amplitudes 2
NASA Astrophysics Data System (ADS)
Denner, Ansgar; Lang, Jean-Nicolas; Uccirati, Sandro
2018-03-01
We present the Fortran95 program RECOLA2 for the perturbative computation of next-to-leading-order transition amplitudes in the Standard Model of particle physics and extended Higgs sectors. New theories are implemented via model files in the 't Hooft-Feynman gauge in the conventional formulation of quantum field theory and in the Background-Field method. The present version includes model files for Two-Higgs-Doublet Model and the Higgs-Singlet Extension of the Standard Model. We support standard renormalization schemes for the Standard Model as well as many commonly used renormalization schemes in extended Higgs sectors. Within these models the computation of next-to-leading-order polarized amplitudes and squared amplitudes, optionally summed over spin and colour, is fully automated for any process. RECOLA2 allows the computation of colour- and spin-correlated leading-order squared amplitudes that are needed in the dipole subtraction formalism. RECOLA2 is publicly available for download at http://recola.hepforge.org.
Modular operads and the quantum open-closed homotopy algebra
NASA Astrophysics Data System (ADS)
Doubek, Martin; Jurčo, Branislav; Münster, Korbinian
2015-12-01
We verify that certain algebras appearing in string field theory are algebras over Feynman transform of modular operads which we describe explicitly. Equivalent description in terms of solutions of generalized BV master equations are explained from the operadic point of view.
Image processing via VLSI: A concept paper
NASA Technical Reports Server (NTRS)
Nathan, R.
1982-01-01
Implementing specific image processing algorithms via very large scale integrated systems offers a potent solution to the problem of handling high data rates. Two algorithms stand out as being particularly critical -- geometric map transformation and filtering or correlation. These two functions form the basis for data calibration, registration and mosaicking. VLSI presents itself as an inexpensive ancillary function to be added to almost any general purpose computer and if the geometry and filter algorithms are implemented in VLSI, the processing rate bottleneck would be significantly relieved. A set of image processing functions that limit present systems to deal with future throughput needs, translates these functions to algorithms, implements via VLSI technology and interfaces the hardware to a general purpose digital computer is developed.
2002-01-01
UNITY program that implements exactly the same algorithm as Specification 1.1. The correctness of this program is proven in amanner sim- 4 program...chapter, we introduce the Dynamic UNITY formalism, which allows us to reason about algorithms and protocols in which the sets of participating processes...implements Euclid’s algorithm for calculating the greatest common divisor (GCD) of two integers; it repeat- edly reads an integer message from each of its
Whitney, Gina; Daves, Suanne; Hughes, Alex; Watkins, Scott; Woods, Marcella; Kreger, Michael; Marincola, Paula; Chocron, Isaac; Donahue, Brian
2013-07-01
The goal of this project is to measure the impact of standardization of transfusion practice on blood product utilization and postoperative bleeding in pediatric cardiac surgery patients. Transfusion is common following cardiopulmonary bypass (CPB) in children and is associated with increased mortality, infection, and duration of mechanical ventilation. Transfusion in pediatric cardiac surgery is often based on clinical judgment rather than objective data. Although objective transfusion algorithms have demonstrated efficacy for reducing transfusion in adult cardiac surgery, such algorithms have not been applied in the pediatric setting. This quality improvement effort was designed to reduce blood product utilization in pediatric cardiac surgery using a blood product transfusion algorithm. We implemented an evidence-based transfusion protocol in January 2011 and monitored the impact of this algorithm on blood product utilization, chest tube output during the first 12 h of intensive care unit (ICU) admission, and predischarge mortality. When compared with the 12 months preceding implementation, blood utilization per case in the operating room odds ratio (OR) for the 11 months following implementation decreased by 66% for red cells (P = 0.001) and 86% for cryoprecipitate (P < 0.001). Blood utilization during the first 12 h of ICU did not increase during this time and actually decreased 56% for plasma (P = 0.006) and 41% for red cells (P = 0.031), indicating that the decrease in OR transfusion did not shift the transfusion burden to the ICU. Postoperative bleeding, as measured by chest tube output in the first 12 ICU hours, did not increase following implementation of the algorithm. Monthly surgical volume did not change significantly following implementation of the algorithm (P = 0.477). In a logistic regression model for predischarge mortality among the nontransplant patients, after accounting for surgical severity and duration of CPB, use of the transfusion algorithm was associated with a 0.247 relative risk of mortality (P = 0.013). These results indicate that introduction of an objective transfusion algorithm in pediatric cardiac surgery significantly reduces perioperative blood product utilization and mortality, without increasing postoperative chest tube losses. © 2013 John Wiley & Sons Ltd.
Resonator reset in circuit QED by optimal control for large open quantum systems
NASA Astrophysics Data System (ADS)
Boutin, Samuel; Andersen, Christian Kraglund; Venkatraman, Jayameenakshi; Ferris, Andrew J.; Blais, Alexandre
2017-10-01
We study an implementation of the open GRAPE (gradient ascent pulse engineering) algorithm well suited for large open quantum systems. While typical implementations of optimal control algorithms for open quantum systems rely on explicit matrix exponential calculations, our implementation avoids these operations, leading to a polynomial speedup of the open GRAPE algorithm in cases of interest. This speedup, as well as the reduced memory requirements of our implementation, are illustrated by comparison to a standard implementation of open GRAPE. As a practical example, we apply this open-system optimization method to active reset of a readout resonator in circuit QED. In this problem, the shape of a microwave pulse is optimized such as to empty the cavity from measurement photons as fast as possible. Using our open GRAPE implementation, we obtain pulse shapes, leading to a reset time over 4 times faster than passive reset.
Implementing the Deutsch-Jozsa algorithm with macroscopic ensembles
NASA Astrophysics Data System (ADS)
Semenenko, Henry; Byrnes, Tim
2016-05-01
Quantum computing implementations under consideration today typically deal with systems with microscopic degrees of freedom such as photons, ions, cold atoms, and superconducting circuits. The quantum information is stored typically in low-dimensional Hilbert spaces such as qubits, as quantum effects are strongest in such systems. It has, however, been demonstrated that quantum effects can be observed in mesoscopic and macroscopic systems, such as nanomechanical systems and gas ensembles. While few-qubit quantum information demonstrations have been performed with such macroscopic systems, a quantum algorithm showing exponential speedup over classical algorithms is yet to be shown. Here, we show that the Deutsch-Jozsa algorithm can be implemented with macroscopic ensembles. The encoding that we use avoids the detrimental effects of decoherence that normally plagues macroscopic implementations. We discuss two mapping procedures which can be chosen depending upon the constraints of the oracle and the experiment. Both methods have an exponential speedup over the classical case, and only require control of the ensembles at the level of the total spin of the ensembles. It is shown that both approaches reproduce the qubit Deutsch-Jozsa algorithm, and are robust under decoherence.
NASA Astrophysics Data System (ADS)
Chan, Garnet Kin-Lic; Keselman, Anna; Nakatani, Naoki; Li, Zhendong; White, Steven R.
2016-07-01
Current descriptions of the ab initio density matrix renormalization group (DMRG) algorithm use two superficially different languages: an older language of the renormalization group and renormalized operators, and a more recent language of matrix product states and matrix product operators. The same algorithm can appear dramatically different when written in the two different vocabularies. In this work, we carefully describe the translation between the two languages in several contexts. First, we describe how to efficiently implement the ab initio DMRG sweep using a matrix product operator based code, and the equivalence to the original renormalized operator implementation. Next we describe how to implement the general matrix product operator/matrix product state algebra within a pure renormalized operator-based DMRG code. Finally, we discuss two improvements of the ab initio DMRG sweep algorithm motivated by matrix product operator language: Hamiltonian compression, and a sum over operators representation that allows for perfect computational parallelism. The connections and correspondences described here serve to link the future developments with the past and are important in the efficient implementation of continuing advances in ab initio DMRG and related algorithms.
A dual-processor multi-frequency implementation of the FINDS algorithm
NASA Technical Reports Server (NTRS)
Godiwala, Pankaj M.; Caglayan, Alper K.
1987-01-01
This report presents a parallel processing implementation of the FINDS (Fault Inferring Nonlinear Detection System) algorithm on a dual processor configured target flight computer. First, a filter initialization scheme is presented which allows the no-fail filter (NFF) states to be initialized using the first iteration of the flight data. A modified failure isolation strategy, compatible with the new failure detection strategy reported earlier, is discussed and the performance of the new FDI algorithm is analyzed using flight recorded data from the NASA ATOPS B-737 aircraft in a Microwave Landing System (MLS) environment. The results show that low level MLS, IMU, and IAS sensor failures are detected and isolated instantaneously, while accelerometer and rate gyro failures continue to take comparatively longer to detect and isolate. The parallel implementation is accomplished by partitioning the FINDS algorithm into two parts: one based on the translational dynamics and the other based on the rotational kinematics. Finally, a multi-rate implementation of the algorithm is presented yielding significantly low execution times with acceptable estimation and FDI performance.
Chan, Garnet Kin-Lic; Keselman, Anna; Nakatani, Naoki; Li, Zhendong; White, Steven R
2016-07-07
Current descriptions of the ab initio density matrix renormalization group (DMRG) algorithm use two superficially different languages: an older language of the renormalization group and renormalized operators, and a more recent language of matrix product states and matrix product operators. The same algorithm can appear dramatically different when written in the two different vocabularies. In this work, we carefully describe the translation between the two languages in several contexts. First, we describe how to efficiently implement the ab initio DMRG sweep using a matrix product operator based code, and the equivalence to the original renormalized operator implementation. Next we describe how to implement the general matrix product operator/matrix product state algebra within a pure renormalized operator-based DMRG code. Finally, we discuss two improvements of the ab initio DMRG sweep algorithm motivated by matrix product operator language: Hamiltonian compression, and a sum over operators representation that allows for perfect computational parallelism. The connections and correspondences described here serve to link the future developments with the past and are important in the efficient implementation of continuing advances in ab initio DMRG and related algorithms.
Multi-jagged: A scalable parallel spatial partitioning algorithm
Deveci, Mehmet; Rajamanickam, Sivasankaran; Devine, Karen D.; ...
2015-03-18
Geometric partitioning is fast and effective for load-balancing dynamic applications, particularly those requiring geometric locality of data (particle methods, crash simulations). We present, to our knowledge, the first parallel implementation of a multidimensional-jagged geometric partitioner. In contrast to the traditional recursive coordinate bisection algorithm (RCB), which recursively bisects subdomains perpendicular to their longest dimension until the desired number of parts is obtained, our algorithm does recursive multi-section with a given number of parts in each dimension. By computing multiple cut lines concurrently and intelligently deciding when to migrate data while computing the partition, we minimize data movement compared to efficientmore » implementations of recursive bisection. We demonstrate the algorithm's scalability and quality relative to the RCB implementation in Zoltan on both real and synthetic datasets. Our experiments show that the proposed algorithm performs and scales better than RCB in terms of run-time without degrading the load balance. Lastly, our implementation partitions 24 billion points into 65,536 parts within a few seconds and exhibits near perfect weak scaling up to 6K cores.« less
NASA Technical Reports Server (NTRS)
Piepmeier, Jeffrey; Mohammed, Priscilla; De Amici, Giovanni; Kim, Edward; Peng, Jinzheng; Ruf, Christopher; Hanna, Maher; Yueh, Simon; Entekhabi, Dara
2016-01-01
The purpose of the Soil Moisture Active Passive (SMAP) radiometer calibration algorithm is to convert Level 0 (L0) radiometer digital counts data into calibrated estimates of brightness temperatures referenced to the Earth's surface within the main beam. The algorithm theory in most respects is similar to what has been developed and implemented for decades for other satellite radiometers; however, SMAP includes two key features heretofore absent from most satellite borne radiometers: radio frequency interference (RFI) detection and mitigation, and measurement of the third and fourth Stokes parameters using digital correlation. The purpose of this document is to describe the SMAP radiometer and forward model, explain the SMAP calibration algorithm, including approximations, errors, and biases, provide all necessary equations for implementing the calibration algorithm and detail the RFI detection and mitigation process. Section 2 provides a summary of algorithm objectives and driving requirements. Section 3 is a description of the instrument and Section 4 covers the forward models, upon which the algorithm is based. Section 5 gives the retrieval algorithm and theory. Section 6 describes the orbit simulator, which implements the forward model and is the key for deriving antenna pattern correction coefficients and testing the overall algorithm.
Finding topological center of a geographic space via road network
NASA Astrophysics Data System (ADS)
Gao, Liang; Miao, Yanan; Qin, Yuhao; Zhao, Xiaomei; Gao, Zi-You
2015-02-01
Previous studies show that the center of a geographic space is of great importance in urban and regional studies, including study of population distribution, urban growth modeling, and scaling properties of urban systems, etc. But how to well define and how to efficiently extract the center of a geographic space are still largely unknown. Recently, Jiang et al. have presented a definition of topological center by their block detection (BD) algorithm. Despite the fact that they first introduced the definition and discovered the 'true center', in human minds, their algorithm left several redundancies in its traversal process. Here, we propose an alternative road-cycle detection (RCD) algorithm to find the topological center, which extracts the outmost road-cycle recursively. To foster the application of the topological center in related research fields, we first reproduce the BD algorithm in Python (pyBD), then implement the RCD algorithm in two ways: the ArcPy implementation (arcRCD) and the Python implementation (pyRCD). After the experiments on twenty-four typical road networks, we find that the results of our RCD algorithm are consistent with those of Jiang's BD algorithm. We also find that the RCD algorithm is at least seven times more efficient than the BD algorithm on all the ten typical road networks.
STAR Algorithm Integration Team - Facilitating operational algorithm development
NASA Astrophysics Data System (ADS)
Mikles, V. J.
2015-12-01
The NOAA/NESDIS Center for Satellite Research and Applications (STAR) provides technical support of the Joint Polar Satellite System (JPSS) algorithm development and integration tasks. Utilizing data from the S-NPP satellite, JPSS generates over thirty Environmental Data Records (EDRs) and Intermediate Products (IPs) spanning atmospheric, ocean, cryosphere, and land weather disciplines. The Algorithm Integration Team (AIT) brings technical expertise and support to product algorithms, specifically in testing and validating science algorithms in a pre-operational environment. The AIT verifies that new and updated algorithms function in the development environment, enforces established software development standards, and ensures that delivered packages are functional and complete. AIT facilitates the development of new JPSS-1 algorithms by implementing a review approach based on the Enterprise Product Lifecycle (EPL) process. Building on relationships established during the S-NPP algorithm development process and coordinating directly with science algorithm developers, the AIT has implemented structured reviews with self-contained document suites. The process has supported algorithm improvements for products such as ozone, active fire, vegetation index, and temperature and moisture profiles.
CPU-GPU hybrid accelerating the Zuker algorithm for RNA secondary structure prediction applications.
Lei, Guoqing; Dou, Yong; Wan, Wen; Xia, Fei; Li, Rongchun; Ma, Meng; Zou, Dan
2012-01-01
Prediction of ribonucleic acid (RNA) secondary structure remains one of the most important research areas in bioinformatics. The Zuker algorithm is one of the most popular methods of free energy minimization for RNA secondary structure prediction. Thus far, few studies have been reported on the acceleration of the Zuker algorithm on general-purpose processors or on extra accelerators such as Field Programmable Gate-Array (FPGA) and Graphics Processing Units (GPU). To the best of our knowledge, no implementation combines both CPU and extra accelerators, such as GPUs, to accelerate the Zuker algorithm applications. In this paper, a CPU-GPU hybrid computing system that accelerates Zuker algorithm applications for RNA secondary structure prediction is proposed. The computing tasks are allocated between CPU and GPU for parallel cooperate execution. Performance differences between the CPU and the GPU in the task-allocation scheme are considered to obtain workload balance. To improve the hybrid system performance, the Zuker algorithm is optimally implemented with special methods for CPU and GPU architecture. Speedup of 15.93× over optimized multi-core SIMD CPU implementation and performance advantage of 16% over optimized GPU implementation are shown in the experimental results. More than 14% of the sequences are executed on CPU in the hybrid system. The system combining CPU and GPU to accelerate the Zuker algorithm is proven to be promising and can be applied to other bioinformatics applications.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Geslot, Benoit; Pepino, Alexandra; Blaise, Patrick
A pile noise measurement campaign has been conducted by the CEA in the VENUS-F reactor (SCK-CEN, Mol Belgium) in April 2011 in the reference critical configuration of the GUINEVERE experimental program. The experimental setup made it possible to estimate the core kinetic parameters: the prompt neutron decay constant, the delayed neutron fraction and the generation time. A precise assessment of these constants is of prime importance. In particular, the effective delayed neutron fraction is used to normalize and compare calculated reactivities of different subcritical configurations, obtained by modifying either the core layout or the control rods position, with experimental onesmore » deduced from the analysis of measurements. This paper presents results obtained with a CEA-developed time stamping acquisition system. Data were analyzed using Rossi-α and Feynman-α methods. Results were normalized to reactor power using a calibrated fission chamber with a deposit of Np-237. Calculated factors were necessary to the analysis: the Diven factor was computed by the ENEA (Italy) and the power calibration factor by the CNRS/IN2P3/LPC Caen. Results deduced with both methods are consistent with respect to calculated quantities. Recommended values are given by the Rossi-α estimator, that was found to be the most robust. The neutron generation time was found equal to 0.438 ± 0.009 μs and the effective delayed neutron fraction is 765 ± 8 pcm. Discrepancies with the calculated value (722 pcm, calculation from ENEA) are satisfactory: -5.6% for the Rossi-α estimate and -2.7% for the Feynman-α estimate. (authors)« less
Salecker-Wigner-Peres clock, Feynman paths, and a tunneling time that should not exist
NASA Astrophysics Data System (ADS)
Sokolovski, D.
2017-08-01
The Salecker-Wigner-Peres (SWP) clock is often used to determine the duration a quantum particle is supposed to spend in a specified region of space Ω . By construction, the result is a real positive number, and the method seems to avoid the difficulty of introducing complex time parameters, which arises in the Feynman paths approach. However, it tells little about the particle's motion. We investigate this matter further, and show that the SWP clock, like any other Larmor clock, correlates the rotation of its angular momentum with the durations τ , which the Feynman paths spend in Ω , thereby destroying interference between different durations. An inaccurate weakly coupled clock leaves the interference almost intact, and the need to resolve the resulting "which way?" problem is one of the main difficulties at the center of the "tunnelling time" controversy. In the absence of a probability distribution for the values of τ , the SWP results are expressed in terms of moduli of the "complex times," given by the weighted sums of the corresponding probability amplitudes. It is shown that overinterpretation of these results, by treating the SWP times as physical time intervals, leads to paradoxes and should be avoided. We also analyze various settings of the SWP clock, different calibration procedures, and the relation between the SWP results and the quantum dwell time. The cases of stationary tunneling and tunnel ionization are considered in some detail. Although our detailed analysis addresses only one particular definition of the duration of a tunneling process, it also points towards the impossibility of uniting various time parameters, which may occur in quantum theory, within the concept of a single tunnelling time.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dongarra, J.J.; Hewitt, T.
1985-08-01
This note describes some experiments on simple, dense linear algebra algorithms. These experiments show that the CRAY X-MP is capable of small-grain multitasking arising from standard implementations of LU and Cholesky decomposition. The implementation described here provides the ''fastest'' execution rate for LU decomposition, 718 MFLOPS for a matrix of order 1000.
Improving energy efficiency in handheld biometric applications
NASA Astrophysics Data System (ADS)
Hoyle, David C.; Gale, John W.; Schultz, Robert C.; Rakvic, Ryan N.; Ives, Robert W.
2012-06-01
With improved smartphone and tablet technology, it is becoming increasingly feasible to implement powerful biometric recognition algorithms on portable devices. Typical iris recognition algorithms, such as Ridge Energy Direction (RED), utilize two-dimensional convolution in their implementation. This paper explores the energy consumption implications of 12 different methods of implementing two-dimensional convolution on a portable device. Typically, convolution is implemented using floating point operations. If a given algorithm implemented integer convolution vice floating point convolution, it could drastically reduce the energy consumed by the processor. The 12 methods compared include 4 major categories: Integer C, Integer Java, Floating Point C, and Floating Point Java. Each major category is further divided into 3 implementations: variable size looped convolution, static size looped convolution, and unrolled looped convolution. All testing was performed using the HTC Thunderbolt with energy measured directly using a Tektronix TDS5104B Digital Phosphor oscilloscope. Results indicate that energy savings as high as 75% are possible by using Integer C versus Floating Point C. Considering the relative proportion of processing time that convolution is responsible for in a typical algorithm, the savings in energy would likely result in significantly greater time between battery charges.
On the VLSI design of a pipeline Reed-Solomon decoder using systolic arrays
NASA Technical Reports Server (NTRS)
Shao, H. M.; Deutsch, L. J.; Reed, I. S.
1987-01-01
A new very large scale integration (VLSI) design of a pipeline Reed-Solomon decoder is presented. The transform decoding technique used in a previous article is replaced by a time domain algorithm through a detailed comparison of their VLSI implementations. A new architecture that implements the time domain algorithm permits efficient pipeline processing with reduced circuitry. Erasure correction capability is also incorporated with little additional complexity. By using a multiplexing technique, a new implementation of Euclid's algorithm maintains the throughput rate with less circuitry. Such improvements result in both enhanced capability and significant reduction in silicon area.
On the VLSI design of a pipeline Reed-Solomon decoder using systolic arrays
NASA Technical Reports Server (NTRS)
Shao, Howard M.; Reed, Irving S.
1988-01-01
A new very large scale integration (VLSI) design of a pipeline Reed-Solomon decoder is presented. The transform decoding technique used in a previous article is replaced by a time domain algorithm through a detailed comparison of their VLSI implementations. A new architecture that implements the time domain algorithm permits efficient pipeline processing with reduced circuitry. Erasure correction capability is also incorporated with little additional complexity. By using multiplexing technique, a new implementation of Euclid's algorithm maintains the throughput rate with less circuitry. Such improvements result in both enhanced capability and significant reduction in silicon area.
NASA Technical Reports Server (NTRS)
Delaat, John C.; Merrill, Walter C.
1990-01-01
The objective of the Advanced Detection, Isolation, and Accommodation Program is to improve the overall demonstrated reliability of digital electronic control systems for turbine engines. For this purpose, an algorithm was developed which detects, isolates, and accommodates sensor failures by using analytical redundancy. The performance of this algorithm was evaluated on a real time engine simulation and was demonstrated on a full scale F100 turbofan engine. The real time implementation of the algorithm is described. The implementation used state-of-the-art microprocessor hardware and software, including parallel processing and high order language programming.
Real-time implementation of logo detection on open source BeagleBoard
NASA Astrophysics Data System (ADS)
George, M.; Kehtarnavaz, N.; Estevez, L.
2011-03-01
This paper presents the real-time implementation of our previously developed logo detection and tracking algorithm on the open source BeagleBoard mobile platform. This platform has an OMAP processor that incorporates an ARM Cortex processor. The algorithm combines Scale Invariant Feature Transform (SIFT) with k-means clustering, online color calibration and moment invariants to robustly detect and track logos in video. Various optimization steps that are carried out to allow the real-time execution of the algorithm on BeagleBoard are discussed. The results obtained are compared to the PC real-time implementation results.
Java implementation of Class Association Rule algorithms
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tamura, Makio
2007-08-30
Java implementation of three Class Association Rule mining algorithms, NETCAR, CARapriori, and clustering based rule mining. NETCAR algorithm is a novel algorithm developed by Makio Tamura. The algorithm is discussed in a paper: UCRL-JRNL-232466-DRAFT, and would be published in a peer review scientific journal. The software is used to extract combinations of genes relevant with a phenotype from a phylogenetic profile and a phenotype profile. The phylogenetic profiles is represented by a binary matrix and a phenotype profile is represented by a binary vector. The present application of this software will be in genome analysis, however, it could be appliedmore » more generally.« less
On distribution reduction and algorithm implementation in inconsistent ordered information systems.
Zhang, Yanqin
2014-01-01
As one part of our work in ordered information systems, distribution reduction is studied in inconsistent ordered information systems (OISs). Some important properties on distribution reduction are studied and discussed. The dominance matrix is restated for reduction acquisition in dominance relations based information systems. Matrix algorithm for distribution reduction acquisition is stepped. And program is implemented by the algorithm. The approach provides an effective tool for the theoretical research and the applications for ordered information systems in practices. For more detailed and valid illustrations, cases are employed to explain and verify the algorithm and the program which shows the effectiveness of the algorithm in complicated information systems.
Super-Encryption Implementation Using Monoalphabetic Algorithm and XOR Algorithm for Data Security
NASA Astrophysics Data System (ADS)
Rachmawati, Dian; Andri Budiman, Mohammad; Aulia, Indra
2018-03-01
The exchange of data that occurs offline and online is very vulnerable to the threat of data theft. In general, cryptography is a science and art to maintain data secrecy. An encryption is a cryptography algorithm in which data is transformed into cipher text, which is something that is unreadable and meaningless so it cannot be read or understood by other parties. In super-encryption, two or more encryption algorithms are combined to make it more secure. In this work, Monoalphabetic algorithm and XOR algorithm are combined to form a super- encryption. Monoalphabetic algorithm works by changing a particular letter into a new letter based on existing keywords while the XOR algorithm works by using logic operation XOR Since Monoalphabetic algorithm is a classical cryptographic algorithm and XOR algorithm is a modern cryptographic algorithm, this scheme is expected to be both easy-to-implement and more secure. The combination of the two algorithms is capable of securing the data and restoring it back to its original form (plaintext), so the data integrity is still ensured.
FGRAAL: FORTRAN extended graph algorithmic language
NASA Technical Reports Server (NTRS)
Basili, V. R.; Mesztenyi, C. K.; Rheinboldt, W. C.
1972-01-01
The FORTRAN version FGRAAL of the graph algorithmic language GRAAL as it has been implemented for the Univac 1108 is described. FBRAAL is an extension of FORTRAN 5 and is intended for describing and implementing graph algorithms of the type primarily arising in applications. The formal description contained in this report represents a supplement to the FORTRAN 5 manual for the Univac 1108 (UP-4060), that is, only the new features of the language are described. Several typical graph algorithms, written in FGRAAL, are included to illustrate various features of the language and to show its applicability.
Pairwise Sequence Alignment Library
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jeff Daily, PNNL
2015-05-20
Vector extensions, such as SSE, have been part of the x86 CPU since the 1990s, with applications in graphics, signal processing, and scientific applications. Although many algorithms and applications can naturally benefit from automatic vectorization techniques, there are still many that are difficult to vectorize due to their dependence on irregular data structures, dense branch operations, or data dependencies. Sequence alignment, one of the most widely used operations in bioinformatics workflows, has a computational footprint that features complex data dependencies. The trend of widening vector registers adversely affects the state-of-the-art sequence alignment algorithm based on striped data layouts. Therefore, amore » novel SIMD implementation of a parallel scan-based sequence alignment algorithm that can better exploit wider SIMD units was implemented as part of the Parallel Sequence Alignment Library (parasail). Parasail features: Reference implementations of all known vectorized sequence alignment approaches. Implementations of Smith Waterman (SW), semi-global (SG), and Needleman Wunsch (NW) sequence alignment algorithms. Implementations across all modern CPU instruction sets including AVX2 and KNC. Language interfaces for C/C++ and Python.« less
Implementation of real-time digital signal processing systems
NASA Technical Reports Server (NTRS)
Narasimha, M.; Peterson, A.; Narayan, S.
1978-01-01
Special purpose hardware implementation of DFT Computers and digital filters is considered in the light of newly introduced algorithms and IC devices. Recent work by Winograd on high-speed convolution techniques for computing short length DFT's, has motivated the development of more efficient algorithms, compared to the FFT, for evaluating the transform of longer sequences. Among these, prime factor algorithms appear suitable for special purpose hardware implementations. Architectural considerations in designing DFT computers based on these algorithms are discussed. With the availability of monolithic multiplier-accumulators, a direct implementation of IIR and FIR filters, using random access memories in place of shift registers, appears attractive. The memory addressing scheme involved in such implementations is discussed. A simple counter set-up to address the data memory in the realization of FIR filters is also described. The combination of a set of simple filters (weighting network) and a DFT computer is shown to realize a bank of uniform bandpass filters. The usefulness of this concept in arriving at a modular design for a million channel spectrum analyzer, based on microprocessors, is discussed.
(NOTE LOCATION) - One West Speaker: Regis Kopper, Duke University Title: Understanding the Benefits of DATE) - One West Speaker: Regina Demina, University of Rochester Title: Top Forward-Backward Asymmetry I play is a very interesting one," says Nobel Laureate Richard Feynman in a low-resolution
The Coupling of Gravity to Spin and Electromagnetism
NASA Astrophysics Data System (ADS)
Finster, Felix; Smoller, Joel; Yau, Shing-Tung
The coupled Einstein-Dirac-Maxwell equations are considered for a static, spherically symmetric system of two fermions in a singlet spinor state. Stable soliton-like solutions are shown to exist, and we discuss the regularizing effect of gravity from a Feynman diagram point of view.
A 3D Split Manufacturing Approach to Trustworthy System Development
2012-12-01
addition of any cryptographic algorithm or implementation to be included in the system as a foundry-level option. Essentially, 3D security introduces...8192 bytes). We modeled our cryptographic process after the AES algorithm , which can occupy up to 4640 bytes with an enlarged T-Box implementation [4...Reconfigurable Systems and Algorithms (ERSA), Las Vegas, NV, July 2011. [10] Intelligence Advanced Research Projects Agency (IARPA). Trusted integrated
Reverse time migration: A seismic processing application on the connection machine
NASA Technical Reports Server (NTRS)
Fiebrich, Rolf-Dieter
1987-01-01
The implementation of a reverse time migration algorithm on the Connection Machine, a massively parallel computer is described. Essential architectural features of this machine as well as programming concepts are presented. The data structures and parallel operations for the implementation of the reverse time migration algorithm are described. The algorithm matches the Connection Machine architecture closely and executes almost at the peak performance of this machine.
NASA Astrophysics Data System (ADS)
Rabemananajara, Tanjona R.; Horowitz, W. A.
2017-09-01
To make predictions for the particle physics processes, one has to compute the cross section of the specific process as this is what one can measure in a modern collider experiment such as the Large Hadron Collider (LHC) at CERN. Theoretically, it has been proven to be extremely difficult to compute scattering amplitudes using conventional methods of Feynman. Calculations with Feynman diagrams are realizations of a perturbative expansion and when doing calculations one has to set up all topologically different diagrams, for a given process up to a given order of coupling in the theory. This quickly makes the calculation of scattering amplitudes a hot mess. Fortunately, one can simplify calculations by considering the helicity amplitude for the Maximally Helicity Violating (MHV). This can be extended to the formalism of on-shell recursion, which is able to derive, in a much simpler way the expression of a high order scattering amplitude from lower orders.
NASA Astrophysics Data System (ADS)
Barnea, A. Ronny; Cheshnovsky, Ori; Even, Uzi
2018-02-01
Interference experiments have been paramount in our understanding of quantum mechanics and are frequently the basis of testing the superposition principle in the framework of quantum theory. In recent years, several studies have challenged the nature of wave-function interference from the perspective of Born's rule—namely, the manifestation of so-called high-order interference terms in a superposition generated by diffraction of the wave functions. Here we present an experimental test of multipath interference in the diffraction of metastable helium atoms, with large-number counting statistics, comparable to photon-based experiments. We use a variation of the original triple-slit experiment and accurate single-event counting techniques to provide a new experimental bound of 2.9 ×10-5 on the statistical deviation from the commonly approximated null third-order interference term in Born's rule for matter waves. Our value is on the order of the maximal contribution predicted for multipath trajectories by Feynman path integrals.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, Jing-Yuan, E-mail: chjy@uchicago.edu; Stanford Institute for Theoretical Physics, Stanford University, CA 94305; Son, Dam Thanh, E-mail: dtson@uchicago.edu
We develop an extension of the Landau Fermi liquid theory to systems of interacting fermions with non-trivial Berry curvature. We propose a kinetic equation and a constitutive relation for the electromagnetic current that together encode the linear response of such systems to external electromagnetic perturbations, to leading and next-to-leading orders in the expansion over the frequency and wave number of the perturbations. We analyze the Feynman diagrams in a large class of interacting quantum field theories and show that, after summing up all orders in perturbation theory, the current–current correlator exactly matches with the result obtained from the kinetic theory.more » - Highlights: • We extend Landau’s kinetic theory of Fermi liquid to incorporate Berry phase. • Berry phase effects in Fermi liquid take exactly the same form as in Fermi gas. • There is a new “emergent electric dipole” contribution to the anomalous Hall effect. • Our kinetic theory is matched to field theory to all orders in Feynman diagrams.« less
Interactions as intertwiners in 4D QFT
NASA Astrophysics Data System (ADS)
de Mello Koch, Robert; Ramgoolam, Sanjaye
2016-03-01
In a recent paper we showed that the correlators of free scalar field theory in four dimensions can be constructed from a two dimensional topological field theory based on so(4 , 2) equivariant maps (intertwiners). The free field result, along with recent results of Frenkel and Libine on equivariance properties of Feynman integrals, are developed further in this paper. We show that the coefficient of the log term in the 1-loop 4-point conformal integral is a projector in the tensor product of so(4 , 2) representations. We also show that the 1-loop 4-point integral can be written as a sum of four terms, each associated with the quantum equation of motion for one of the four external legs. The quantum equation of motion is shown to be related to equivariant maps involving indecomposable representations of so(4 , 2), a phenomenon which illuminates multiplet recombination. The harmonic expansion method for Feynman integrals is a powerful tool for arriving at these results. The generalization to other interactions and higher loops is discussed.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Coffey, Mark W.
2008-04-15
Perturbative quantum field theory for the Ising model at the three-loop level yields a tetrahedral Feynman diagram C(a,b) with masses a and b and four other lines with unit mass. The completely symmetric tetrahedron C{sup Tet}{identical_to}C(1,1) has been of interest from many points of view, with several representations and conjectures having been given in the literature. We prove a conjectured exponentially fast convergent sum for C(1,1), as well as a previously empirical relation for C(1,1) as a remarkable difference of Clausen function values. Our presentation includes propositions extending the theory of the dilogarithm Li{sub 2} and Clausen Cl{sub 2} functions,more » as well as their relation to other special functions of mathematical physics. The results strengthen connections between Feynman diagram integrals, volumes in hyperbolic space, number theory, and special functions and numbers, specifically including dilogarithms, Clausen function values, and harmonic numbers.« less
NASA Astrophysics Data System (ADS)
Accioly, Antonio; Helayël-Neto, José; Barone, F. E.; Herdy, Wallace
2015-02-01
A straightforward prescription for computing the D-dimensional potential energy of gravitational models, which is strongly based on the Feynman path integral, is built up. Using this method, the static potential energy for the interaction of two masses is found in the context of D-dimensional higher-derivative gravity models, and its behavior is analyzed afterwards in both ultraviolet and infrared regimes. As a consequence, two new gravity systems in which the potential energy is finite at the origin, respectively, in D = 5 and D = 6, are found. Since the aforementioned prescription is equivalent to that based on the marriage between quantum mechanics (to leading order, i.e., in the first Born approximation) and the nonrelativistic limit of quantum field theory, and bearing in mind that the latter relies basically on the calculation of the nonrelativistic Feynman amplitude ({{M}NR}), a trivial expression for computing {{M}NR} is obtained from our prescription as an added bonus.
ODTbrain: a Python library for full-view, dense diffraction tomography.
Müller, Paul; Schürmann, Mirjam; Guck, Jochen
2015-11-04
Analyzing the three-dimensional (3D) refractive index distribution of a single cell makes it possible to describe and characterize its inner structure in a marker-free manner. A dense, full-view tomographic data set is a set of images of a cell acquired for multiple rotational positions, densely distributed from 0 to 360 degrees. The reconstruction is commonly realized by projection tomography, which is based on the inversion of the Radon transform. The reconstruction quality of projection tomography is greatly improved when first order scattering, which becomes relevant when the imaging wavelength is comparable to the characteristic object size, is taken into account. This advanced reconstruction technique is called diffraction tomography. While many implementations of projection tomography are available today, there is no publicly available implementation of diffraction tomography so far. We present a Python library that implements the backpropagation algorithm for diffraction tomography in 3D. By establishing benchmarks based on finite-difference time-domain (FDTD) simulations, we showcase the superiority of the backpropagation algorithm over the backprojection algorithm. Furthermore, we discuss how measurment parameters influence the reconstructed refractive index distribution and we also give insights into the applicability of diffraction tomography to biological cells. The present software library contains a robust implementation of the backpropagation algorithm. The algorithm is ideally suited for the application to biological cells. Furthermore, the implementation is a drop-in replacement for the classical backprojection algorithm and is made available to the large user community of the Python programming language.
Implementation and performance of shutterless uncooled micro-bolometer cameras
NASA Astrophysics Data System (ADS)
Das, J.; de Gaspari, D.; Cornet, P.; Deroo, P.; Vermeiren, J.; Merken, P.
2015-06-01
A shutterless algorithm is implemented into the Xenics LWIR thermal cameras and modules. Based on a calibration set and a global temperature coefficient the optimal non-uniformity correction is calculated onboard of the camera. The limited resources in the camera require a compact algorithm, hence the efficiency of the coding is important. The performance of the shutterless algorithm is studied by a comparison of the residual non-uniformity (RNU) and signal-to-noise ratio (SNR) between the shutterless and shuttered correction algorithm. From this comparison we conclude that the shutterless correction is only slightly less performant compared to the standard shuttered algorithm, making this algorithm very interesting for thermal infrared applications where small weight and size, and continuous operation are important.
NASA Astrophysics Data System (ADS)
Zhang, Zhenhai; Li, Kejie; Wu, Xiaobing; Zhang, Shujiang
2008-03-01
The unwrapped and correcting algorithm based on Coordinate Rotation Digital Computer (CORDIC) and bilinear interpolation algorithm was presented in this paper, with the purpose of processing dynamic panoramic annular image. An original annular panoramic image captured by panoramic annular lens (PAL) can be unwrapped and corrected to conventional rectangular image without distortion, which is much more coincident with people's vision. The algorithm for panoramic image processing is modeled by VHDL and implemented in FPGA. The experimental results show that the proposed panoramic image algorithm for unwrapped and distortion correction has the lower computation complexity and the architecture for dynamic panoramic image processing has lower hardware cost and power consumption. And the proposed algorithm is valid.
Memetic algorithms for de novo motif-finding in biomedical sequences.
Bi, Chengpeng
2012-09-01
The objectives of this study are to design and implement a new memetic algorithm for de novo motif discovery, which is then applied to detect important signals hidden in various biomedical molecular sequences. In this paper, memetic algorithms are developed and tested in de novo motif-finding problems. Several strategies in the algorithm design are employed that are to not only efficiently explore the multiple sequence local alignment space, but also effectively uncover the molecular signals. As a result, there are a number of key features in the implementation of the memetic motif-finding algorithm (MaMotif), including a chromosome replacement operator, a chromosome alteration-aware local search operator, a truncated local search strategy, and a stochastic operation of local search imposed on individual learning. To test the new algorithm, we compare MaMotif with a few of other similar algorithms using simulated and experimental data including genomic DNA, primary microRNA sequences (let-7 family), and transmembrane protein sequences. The new memetic motif-finding algorithm is successfully implemented in C++, and exhaustively tested with various simulated and real biological sequences. In the simulation, it shows that MaMotif is the most time-efficient algorithm compared with others, that is, it runs 2 times faster than the expectation maximization (EM) method and 16 times faster than the genetic algorithm-based EM hybrid. In both simulated and experimental testing, results show that the new algorithm is compared favorably or superior to other algorithms. Notably, MaMotif is able to successfully discover the transcription factors' binding sites in the chromatin immunoprecipitation followed by massively parallel sequencing (ChIP-Seq) data, correctly uncover the RNA splicing signals in gene expression, and precisely find the highly conserved helix motif in the transmembrane protein sequences, as well as rightly detect the palindromic segments in the primary microRNA sequences. The memetic motif-finding algorithm is effectively designed and implemented, and its applications demonstrate it is not only time-efficient, but also exhibits excellent performance while compared with other popular algorithms. Copyright © 2012 Elsevier B.V. All rights reserved.
Hardware Implementation of Maximum Power Point Tracking for Thermoelectric Generators
NASA Astrophysics Data System (ADS)
Maganga, Othman; Phillip, Navneesh; Burnham, Keith J.; Montecucco, Andrea; Siviter, Jonathan; Knox, Andrew; Simpson, Kevin
2014-06-01
This work describes the practical implementation of two maximum power point tracking (MPPT) algorithms, namely those of perturb and observe, and extremum seeking control. The proprietary dSPACE system is used to perform hardware in the loop (HIL) simulation whereby the two control algorithms are implemented using the MATLAB/Simulink (Mathworks, Natick, MA) software environment in order to control a synchronous buck-boost converter connected to two commercial thermoelectric modules. The process of performing HIL simulation using dSPACE is discussed, and a comparison between experimental and simulated results is highlighted. The experimental results demonstrate the validity of the two MPPT algorithms, and in conclusion the benefits and limitations of real-time implementation of MPPT controllers using dSPACE are discussed.
VLSI implementation of RSA encryption system using ancient Indian Vedic mathematics
NASA Astrophysics Data System (ADS)
Thapliyal, Himanshu; Srinivas, M. B.
2005-06-01
This paper proposes the hardware implementation of RSA encryption/decryption algorithm using the algorithms of Ancient Indian Vedic Mathematics that have been modified to improve performance. The recently proposed hierarchical overlay multiplier architecture is used in the RSA circuitry for multiplication operation. The most significant aspect of the paper is the development of a division architecture based on Straight Division algorithm of Ancient Indian Vedic Mathematics and embedding it in RSA encryption/decryption circuitry for improved efficiency. The coding is done in Verilog HDL and the FPGA synthesis is done using Xilinx Spartan library. The results show that RSA circuitry implemented using Vedic division and multiplication is efficient in terms of area/speed compared to its implementation using conventional multiplication and division architectures.
NASA Astrophysics Data System (ADS)
García, Aday; Santos, Lucana; López, Sebastián.; Callicó, Gustavo M.; Lopez, Jose F.; Sarmiento, Roberto
2014-05-01
Efficient onboard satellite hyperspectral image compression represents a necessity and a challenge for current and future space missions. Therefore, it is mandatory to provide hardware implementations for this type of algorithms in order to achieve the constraints required for onboard compression. In this work, we implement the Lossy Compression for Exomars (LCE) algorithm on an FPGA by means of high-level synthesis (HSL) in order to shorten the design cycle. Specifically, we use CatapultC HLS tool to obtain a VHDL description of the LCE algorithm from C-language specifications. Two different approaches are followed for HLS: on one hand, introducing the whole C-language description in CatapultC and on the other hand, splitting the C-language description in functional modules to be implemented independently with CatapultC, connecting and controlling them by an RTL description code without HLS. In both cases the goal is to obtain an FPGA implementation. We explain the several changes applied to the original Clanguage source code in order to optimize the results obtained by CatapultC for both approaches. Experimental results show low area occupancy of less than 15% for a SRAM-based Virtex-5 FPGA and a maximum frequency above 80 MHz. Additionally, the LCE compressor was implemented into an RTAX2000S antifuse-based FPGA, showing an area occupancy of 75% and a frequency around 53 MHz. All these serve to demonstrate that the LCE algorithm can be efficiently executed on an FPGA onboard a satellite. A comparison between both implementation approaches is also provided. The performance of the algorithm is finally compared with implementations on other technologies, specifically a graphics processing unit (GPU) and a single-threaded CPU.
Fast and Adaptive Lossless Onboard Hyperspectral Data Compression System
NASA Technical Reports Server (NTRS)
Aranki, Nazeeh I.; Keymeulen, Didier; Kimesh, Matthew A.
2012-01-01
Modern hyperspectral imaging systems are able to acquire far more data than can be downlinked from a spacecraft. Onboard data compression helps to alleviate this problem, but requires a system capable of power efficiency and high throughput. Software solutions have limited throughput performance and are power-hungry. Dedicated hardware solutions can provide both high throughput and power efficiency, while taking the load off of the main processor. Thus a hardware compression system was developed. The implementation uses a field-programmable gate array (FPGA). The implementation is based on the fast lossless (FL) compression algorithm reported in Fast Lossless Compression of Multispectral-Image Data (NPO-42517), NASA Tech Briefs, Vol. 30, No. 8 (August 2006), page 26, which achieves excellent compression performance and has low complexity. This algorithm performs predictive compression using an adaptive filtering method, and uses adaptive Golomb coding. The implementation also packetizes the coded data. The FL algorithm is well suited for implementation in hardware. In the FPGA implementation, one sample is compressed every clock cycle, which makes for a fast and practical realtime solution for space applications. Benefits of this implementation are: 1) The underlying algorithm achieves a combination of low complexity and compression effectiveness that exceeds that of techniques currently in use. 2) The algorithm requires no training data or other specific information about the nature of the spectral bands for a fixed instrument dynamic range. 3) Hardware acceleration provides a throughput improvement of 10 to 100 times vs. the software implementation. A prototype of the compressor is available in software, but it runs at a speed that does not meet spacecraft requirements. The hardware implementation targets the Xilinx Virtex IV FPGAs, and makes the use of this compressor practical for Earth satellites as well as beyond-Earth missions with hyperspectral instruments.
Parallel grid generation algorithm for distributed memory computers
NASA Technical Reports Server (NTRS)
Moitra, Stuti; Moitra, Anutosh
1994-01-01
A parallel grid-generation algorithm and its implementation on the Intel iPSC/860 computer are described. The grid-generation scheme is based on an algebraic formulation of homotopic relations. Methods for utilizing the inherent parallelism of the grid-generation scheme are described, and implementation of multiple levELs of parallelism on multiple instruction multiple data machines are indicated. The algorithm is capable of providing near orthogonality and spacing control at solid boundaries while requiring minimal interprocessor communications. Results obtained on the Intel hypercube for a blended wing-body configuration are used to demonstrate the effectiveness of the algorithm. Fortran implementations bAsed on the native programming model of the iPSC/860 computer and the Express system of software tools are reported. Computational gains in execution time speed-up ratios are given.
Empirical study of parallel LRU simulation algorithms
NASA Technical Reports Server (NTRS)
Carr, Eric; Nicol, David M.
1994-01-01
This paper reports on the performance of five parallel algorithms for simulating a fully associative cache operating under the LRU (Least-Recently-Used) replacement policy. Three of the algorithms are SIMD, and are implemented on the MasPar MP-2 architecture. Two other algorithms are parallelizations of an efficient serial algorithm on the Intel Paragon. One SIMD algorithm is quite simple, but its cost is linear in the cache size. The two other SIMD algorithm are more complex, but have costs that are independent on the cache size. Both the second and third SIMD algorithms compute all stack distances; the second SIMD algorithm is completely general, whereas the third SIMD algorithm presumes and takes advantage of bounds on the range of reference tags. Both MIMD algorithm implemented on the Paragon are general and compute all stack distances; they differ in one step that may affect their respective scalability. We assess the strengths and weaknesses of these algorithms as a function of problem size and characteristics, and compare their performance on traces derived from execution of three SPEC benchmark programs.
NASA Astrophysics Data System (ADS)
Tolson, B.; Matott, L. S.; Gaffoor, T. A.; Asadzadeh, M.; Shafii, M.; Pomorski, P.; Xu, X.; Jahanpour, M.; Razavi, S.; Haghnegahdar, A.; Craig, J. R.
2015-12-01
We introduce asynchronous parallel implementations of the Dynamically Dimensioned Search (DDS) family of algorithms including DDS, discrete DDS, PA-DDS and DDS-AU. These parallel algorithms are unique from most existing parallel optimization algorithms in the water resources field in that parallel DDS is asynchronous and does not require an entire population (set of candidate solutions) to be evaluated before generating and then sending a new candidate solution for evaluation. One key advance in this study is developing the first parallel PA-DDS multi-objective optimization algorithm. The other key advance is enhancing the computational efficiency of solving optimization problems (such as model calibration) by combining a parallel optimization algorithm with the deterministic model pre-emption concept. These two efficiency techniques can only be combined because of the asynchronous nature of parallel DDS. Model pre-emption functions to terminate simulation model runs early, prior to completely simulating the model calibration period for example, when intermediate results indicate the candidate solution is so poor that it will definitely have no influence on the generation of further candidate solutions. The computational savings of deterministic model preemption available in serial implementations of population-based algorithms (e.g., PSO) disappear in synchronous parallel implementations as these algorithms. In addition to the key advances above, we implement the algorithms across a range of computation platforms (Windows and Unix-based operating systems from multi-core desktops to a supercomputer system) and package these for future modellers within a model-independent calibration software package called Ostrich as well as MATLAB versions. Results across multiple platforms and multiple case studies (from 4 to 64 processors) demonstrate the vast improvement over serial DDS-based algorithms and highlight the important role model pre-emption plays in the performance of parallel, pre-emptable DDS algorithms. Case studies include single- and multiple-objective optimization problems in water resources model calibration and in many cases linear or near linear speedups are observed.
Accelerating DNA analysis applications on GPU clusters
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tumeo, Antonino; Villa, Oreste
DNA analysis is an emerging application of high performance bioinformatic. Modern sequencing machinery are able to provide, in few hours, large input streams of data which needs to be matched against exponentially growing databases known fragments. The ability to recognize these patterns effectively and fastly may allow extending the scale and the reach of the investigations performed by biology scientists. Aho-Corasick is an exact, multiple pattern matching algorithm often at the base of this application. High performance systems are a promising platform to accelerate this algorithm, which is computationally intensive but also inherently parallel. Nowadays, high performance systems also includemore » heterogeneous processing elements, such as Graphic Processing Units (GPUs), to further accelerate parallel algorithms. Unfortunately, the Aho-Corasick algorithm exhibits large performance variabilities, depending on the size of the input streams, on the number of patterns to search and on the number of matches, and poses significant challenges on current high performance software and hardware implementations. An adequate mapping of the algorithm on the target architecture, coping with the limit of the underlining hardware, is required to reach the desired high throughputs. Load balancing also plays a crucial role when considering the limited bandwidth among the nodes of these systems. In this paper we present an efficient implementation of the Aho-Corasick algorithm for high performance clusters accelerated with GPUs. We discuss how we partitioned and adapted the algorithm to fit the Tesla C1060 GPU and then present a MPI based implementation for a heterogeneous high performance cluster. We compare this implementation to MPI and MPI with pthreads based implementations for a homogeneous cluster of x86 processors, discussing the stability vs. the performance and the scaling of the solutions, taking into consideration aspects such as the bandwidth among the different nodes.« less
Development and Testing of Data Mining Algorithms for Earth Observation
NASA Technical Reports Server (NTRS)
Glymour, Clark
2005-01-01
The new algorithms developed under this project included a principled procedure for classification of objects, events or circumstances according to a target variable when a very large number of potential predictor variables is available but the number of cases that can be used for training a classifier is relatively small. These "high dimensional" problems require finding a minimal set of variables -called the Markov Blanket-- sufficient for predicting the value of the target variable. An algorithm, the Markov Blanket Fan Search, was developed, implemented and tested on both simulated and real data in conjunction with a graphical model classifier, which was also implemented. Another algorithm developed and implemented in TETRAD IV for time series elaborated on work by C. Granger and N. Swanson, which in turn exploited some of our earlier work. The algorithms in question learn a linear time series model from data. Given such a time series, the simultaneous residual covariances, after factoring out time dependencies, may provide information about causal processes that occur more rapidly than the time series representation allow, so called simultaneous or contemporaneous causal processes. Working with A. Monetta, a graduate student from Italy, we produced the correct statistics for estimating the contemporaneous causal structure from time series data using the TETRAD IV suite of algorithms. Two economists, David Bessler and Kevin Hoover, have independently published applications using TETRAD style algorithms to the same purpose. These implementations and algorithmic developments were separately used in two kinds of studies of climate data: Short time series of geographically proximate climate variables predicting agricultural effects in California, and longer duration climate measurements of temperature teleconnections.
"Symptom-based insulin adjustment for glucose normalization" (SIGN) algorithm: a pilot study.
Lee, Joyce Yu-Chia; Tsou, Keith; Lim, Jiahui; Koh, Feaizen; Ong, Sooim; Wong, Sabrina
2012-12-01
Lack of self-monitoring of blood glucose (SMBG) records in actual practice settings continues to create therapeutic challenges for clinicians, especially in adjusting insulin therapy. In order to overcome this clinical obstacle, a "Symptom-based Insulin adjustment for Glucose Normalization" (SIGN) algorithm was developed to guide clinicians in caring for patients with uncontrolled type 2 diabetes who have few to no SMBG records. This study examined the clinical outcome and safety of the SIGN algorithm. Glycated hemoglobin (HbA1c), insulin usage, and insulin-related adverse effects of a total of 114 patients with uncontrolled type 2 diabetes who refused to use SMBG or performed SMBG once a day for less than three times per week were studied 3 months prior to the implementation of the algorithm and prospectively at every 3-month interval for a total of 6 months after the algorithm implementation. Patients with type 1 diabetes, nonadherence to diabetes medications, or who were not on insulin therapy at any time during the study period were excluded from this study. Mean HbA1c improved by 0.29% at 3 months (P = 0.015) and 0.41% at 6 months (P = 0.006) after algorithm implementation. A slight increase in HbA1c was observed when the algorithm was not implemented. There were no major hypoglycemic episodes. The number of minor hypoglycemic episodes was minimal with the majority of the cases due to irregular meal habits. The SIGN algorithm appeared to offer a viable and safe approach when managing uncontrolled patients with type 2 diabetes who have few to no SMBG records.
Parallelization and implementation of approximate root isolation for nonlinear system by Monte Carlo
NASA Astrophysics Data System (ADS)
Khosravi, Ebrahim
1998-12-01
This dissertation solves a fundamental problem of isolating the real roots of nonlinear systems of equations by Monte-Carlo that were published by Bush Jones. This algorithm requires only function values and can be applied readily to complicated systems of transcendental functions. The implementation of this sequential algorithm provides scientists with the means to utilize function analysis in mathematics or other fields of science. The algorithm, however, is so computationally intensive that the system is limited to a very small set of variables, and this will make it unfeasible for large systems of equations. Also a computational technique was needed for investigating a metrology of preventing the algorithm structure from converging to the same root along different paths of computation. The research provides techniques for improving the efficiency and correctness of the algorithm. The sequential algorithm for this technique was corrected and a parallel algorithm is presented. This parallel method has been formally analyzed and is compared with other known methods of root isolation. The effectiveness, efficiency, enhanced overall performance of the parallel processing of the program in comparison to sequential processing is discussed. The message passing model was used for this parallel processing, and it is presented and implemented on Intel/860 MIMD architecture. The parallel processing proposed in this research has been implemented in an ongoing high energy physics experiment: this algorithm has been used to track neutrinoes in a super K detector. This experiment is located in Japan, and data can be processed on-line or off-line locally or remotely.
Algorithms and programming tools for image processing on the MPP:3
NASA Technical Reports Server (NTRS)
Reeves, Anthony P.
1987-01-01
This is the third and final report on the work done for NASA Grant 5-403 on Algorithms and Programming Tools for Image Processing on the MPP:3. All the work done for this grant is summarized in the introduction. Work done since August 1986 is reported in detail. Research for this grant falls under the following headings: (1) fundamental algorithms for the MPP; (2) programming utilities for the MPP; (3) the Parallel Pascal Development System; and (4) performance analysis. In this report, the results of two efforts are reported: region growing, and performance analysis of important characteristic algorithms. In each case, timing results from MPP implementations are included. A paper is included in which parallel algorithms for region growing on the MPP is discussed. These algorithms permit different sized regions to be merged in parallel. Details on the implementation and peformance of several important MPP algorithms are given. These include a number of standard permutations, the FFT, convolution, arbitrary data mappings, image warping, and pyramid operations, all of which have been implemented on the MPP. The permutation and image warping functions have been included in the standard development system library.
Peng, Bo; Wang, Yuqi; Hall, Timothy J; Jiang, Jingfeng
2017-04-01
Our primary objective of this paper was to extend a previously published 2-D coupled subsample tracking algorithm for 3-D speckle tracking in the framework of ultrasound breast strain elastography. In order to overcome heavy computational cost, we investigated the use of a graphic processing unit (GPU) to accelerate the 3-D coupled subsample speckle tracking method. The performance of the proposed GPU implementation was tested using a tissue-mimicking phantom and in vivo breast ultrasound data. The performance of this 3-D subsample tracking algorithm was compared with the conventional 3-D quadratic subsample estimation algorithm. On the basis of these evaluations, we concluded that the GPU implementation of this 3-D subsample estimation algorithm can provide high-quality strain data (i.e., high correlation between the predeformation and the motion-compensated postdeformation radio frequency echo data and high contrast-to-noise ratio strain images), as compared with the conventional 3-D quadratic subsample algorithm. Using the GPU implementation of the 3-D speckle tracking algorithm, volumetric strain data can be achieved relatively fast (approximately 20 s per volume [2.5 cm ×2.5 cm ×2.5 cm]).
Computing rank-revealing QR factorizations of dense matrices.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bischof, C. H.; Quintana-Orti, G.; Mathematics and Computer Science
1998-06-01
We develop algorithms and implementations for computing rank-revealing QR (RRQR) factorizations of dense matrices. First, we develop an efficient block algorithm for approximating an RRQR factorization, employing a windowed version of the commonly used Golub pivoting strategy, aided by incremental condition estimation. Second, we develop efficiently implementable variants of guaranteed reliable RRQR algorithms for triangular matrices originally suggested by Chandrasekaran and Ipsen and by Pan and Tang. We suggest algorithmic improvements with respect to condition estimation, termination criteria, and Givens updating. By combining the block algorithm with one of the triangular postprocessing steps, we arrive at an efficient and reliablemore » algorithm for computing an RRQR factorization of a dense matrix. Experimental results on IBM RS/6000 SGI R8000 platforms show that this approach performs up to three times faster that the less reliable QR factorization with column pivoting as it is currently implemented in LAPACK, and comes within 15% of the performance of the LAPACK block algorithm for computing a QR factorization without any column exchanges. Thus, we expect this routine to be useful in may circumstances where numerical rank deficiency cannot be ruled out, but currently has been ignored because of the computational cost of dealing with it.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Qin, SB; Cady, ST; Dominguez-Garcia, AD
This paper presents the theory and implementation of a distributed algorithm for controlling differential power processing converters in photovoltaic (PV) applications. This distributed algorithm achieves true maximum power point tracking of series-connected PV submodules by relying only on local voltage measurements and neighbor-to-neighbor communication between the differential power converters. Compared to previous solutions, the proposed algorithm achieves reduced number of perturbations at each step and potentially faster tracking without adding extra hardware; all these features make this algorithm well-suited for long submodule strings. The formulation of the algorithm, discussion of its properties, as well as three case studies are presented.more » The performance of the distributed tracking algorithm has been verified via experiments, which yielded quantifiable improvements over other techniques that have been implemented in practice. Both simulations and hardware experiments have confirmed the effectiveness of the proposed distributed algorithm.« less
Ozmutlu, H. Cenk
2014-01-01
We developed mixed integer programming (MIP) models and hybrid genetic-local search algorithms for the scheduling problem of unrelated parallel machines with job sequence and machine-dependent setup times and with job splitting property. The first contribution of this paper is to introduce novel algorithms which make splitting and scheduling simultaneously with variable number of subjobs. We proposed simple chromosome structure which is constituted by random key numbers in hybrid genetic-local search algorithm (GAspLA). Random key numbers are used frequently in genetic algorithms, but it creates additional difficulty when hybrid factors in local search are implemented. We developed algorithms that satisfy the adaptation of results of local search into the genetic algorithms with minimum relocation operation of genes' random key numbers. This is the second contribution of the paper. The third contribution of this paper is three developed new MIP models which are making splitting and scheduling simultaneously. The fourth contribution of this paper is implementation of the GAspLAMIP. This implementation let us verify the optimality of GAspLA for the studied combinations. The proposed methods are tested on a set of problems taken from the literature and the results validate the effectiveness of the proposed algorithms. PMID:24977204
Recursive Implementations of the Consider Filter
NASA Technical Reports Server (NTRS)
Zanetti, Renato; DSouza, Chris
2012-01-01
One method to account for parameters errors in the Kalman filter is to consider their effect in the so-called Schmidt-Kalman filter. This work addresses issues that arise when implementing a consider Kalman filter as a real-time, recursive algorithm. A favorite implementation of the Kalman filter as an onboard navigation subsystem is the UDU formulation. A new way to implement a UDU consider filter is proposed. The non-optimality of the recursive consider filter is also analyzed, and a modified algorithm is proposed to overcome this limitation.
Reduced Order Model Basis Vector Generation: Generates Basis Vectors fro ROMs
DOE Office of Scientific and Technical Information (OSTI.GOV)
Arrighi, Bill
2016-03-03
libROM is a library that implements order reduction via singular value decomposition (SVD) of sampled state vectors. It implements 2 parallel, incremental SVD algorithms and one serial, non-incremental algorithm. It also provides a mechanism for adaptive sampling of basis vectors.
FPGA based hardware optimized implementation of signal processing system for LFM pulsed radar
NASA Astrophysics Data System (ADS)
Azim, Noor ul; Jun, Wang
2016-11-01
Signal processing is one of the main parts of any radar system. Different signal processing algorithms are used to extract information about different parameters like range, speed, direction etc, of a target in the field of radar communication. This paper presents LFM (Linear Frequency Modulation) pulsed radar signal processing algorithms which are used to improve target detection, range resolution and to estimate the speed of a target. Firstly, these algorithms are simulated in MATLAB to verify the concept and theory. After the conceptual verification in MATLAB, the simulation is converted into implementation on hardware using Xilinx FPGA. Chosen FPGA is Xilinx Virtex-6 (XC6LVX75T). For hardware implementation pipeline optimization is adopted and also other factors are considered for resources optimization in the process of implementation. Focusing algorithms in this work for improving target detection, range resolution and speed estimation are hardware optimized fast convolution processing based pulse compression and pulse Doppler processing.
A Robustly Stabilizing Model Predictive Control Algorithm
NASA Technical Reports Server (NTRS)
Ackmece, A. Behcet; Carson, John M., III
2007-01-01
A model predictive control (MPC) algorithm that differs from prior MPC algorithms has been developed for controlling an uncertain nonlinear system. This algorithm guarantees the resolvability of an associated finite-horizon optimal-control problem in a receding-horizon implementation.
Enforcing Memory Policy Specifications in Reconfigurable Hardware
2008-10-01
we explain the algorithms behind our reference monitor design flow. In Section 4, we describe our access policy language including several example...NFA from this regular expression using Thompson’s Algorithm [1] as implemented by Gerzic [19]. Figure 4 shows the NFA for our policy. Notice that the... Algorithm [1] as implemented by Grail [49] to minimize the DFA. Figure 5 shows the minimized DFA for our policy. Processing the Ranges Before we can
Yang, Changju; Kim, Hyongsuk; Adhikari, Shyam Prasad; Chua, Leon O.
2016-01-01
A hybrid learning method of a software-based backpropagation learning and a hardware-based RWC learning is proposed for the development of circuit-based neural networks. The backpropagation is known as one of the most efficient learning algorithms. A weak point is that its hardware implementation is extremely difficult. The RWC algorithm, which is very easy to implement with respect to its hardware circuits, takes too many iterations for learning. The proposed learning algorithm is a hybrid one of these two. The main learning is performed with a software version of the BP algorithm, firstly, and then, learned weights are transplanted on a hardware version of a neural circuit. At the time of the weight transplantation, a significant amount of output error would occur due to the characteristic difference between the software and the hardware. In the proposed method, such error is reduced via a complementary learning of the RWC algorithm, which is implemented in a simple hardware. The usefulness of the proposed hybrid learning system is verified via simulations upon several classical learning problems. PMID:28025566
Improving family satisfaction and participation in decision making in an intensive care unit.
Huffines, Meredith; Johnson, Karen L; Smitz Naranjo, Linda L; Lissauer, Matthew E; Fishel, Marmie Ann-Michelle; D'Angelo Howes, Susan M; Pannullo, Diane; Ralls, Mindy; Smith, Ruth
2013-10-01
Background Survey data revealed that families of patients in a surgical intensive care unit were not satisfied with their participation in decision making or with how well the multidisciplinary team worked together. Objectives To develop and implement an evidence-based communication algorithm and evaluate its effect in improving satisfaction among patients' families. Methods A multidisciplinary team developed an algorithm that included bundles of communication interventions at 24, 72, and 96 hours after admission to the unit. The algorithm included clinical triggers, which if present escalated the algorithm. A pre-post design using process improvement methods was used to compare families' satisfaction scores before and after implementation of the algorithm. Results Satisfaction scores for participation in decision making (45% vs 68%; z = -2.62, P = .009) and how well the health care team worked together (64% vs 83%; z = -2.10, P = .04) improved significantly after implementation. Conclusions Use of an evidence-based structured communication algorithm may be a way to improve satisfaction of families of intensive care patients with their participation in decision making and their perception of how well the unit's team works together.
Implementation and analysis of a Navier-Stokes algorithm on parallel computers
NASA Technical Reports Server (NTRS)
Fatoohi, Raad A.; Grosch, Chester E.
1988-01-01
The results of the implementation of a Navier-Stokes algorithm on three parallel/vector computers are presented. The object of this research is to determine how well, or poorly, a single numerical algorithm would map onto three different architectures. The algorithm is a compact difference scheme for the solution of the incompressible, two-dimensional, time-dependent Navier-Stokes equations. The computers were chosen so as to encompass a variety of architectures. They are the following: the MPP, an SIMD machine with 16K bit serial processors; Flex/32, an MIMD machine with 20 processors; and Cray/2. The implementation of the algorithm is discussed in relation to these architectures and measures of the performance on each machine are given. The basic comparison is among SIMD instruction parallelism on the MPP, MIMD process parallelism on the Flex/32, and vectorization of a serial code on the Cray/2. Simple performance models are used to describe the performance. These models highlight the bottlenecks and limiting factors for this algorithm on these architectures. Finally, conclusions are presented.
Angle Statistics Reconstruction: a robust reconstruction algorithm for Muon Scattering Tomography
NASA Astrophysics Data System (ADS)
Stapleton, M.; Burns, J.; Quillin, S.; Steer, C.
2014-11-01
Muon Scattering Tomography (MST) is a technique for using the scattering of cosmic ray muons to probe the contents of enclosed volumes. As a muon passes through material it undergoes multiple Coulomb scattering, where the amount of scattering is dependent on the density and atomic number of the material as well as the path length. Hence, MST has been proposed as a means of imaging dense materials, for instance to detect special nuclear material in cargo containers. Algorithms are required to generate an accurate reconstruction of the material density inside the volume from the muon scattering information and some have already been proposed, most notably the Point of Closest Approach (PoCA) and Maximum Likelihood/Expectation Maximisation (MLEM) algorithms. However, whilst PoCA-based algorithms are easy to implement, they perform rather poorly in practice. Conversely, MLEM is a complicated algorithm to implement and computationally intensive and there is currently no published, fast and easily-implementable algorithm that performs well in practice. In this paper, we first provide a detailed analysis of the source of inaccuracy in PoCA-based algorithms. We then motivate an alternative method, based on ideas first laid out by Morris et al, presenting and fully specifying an algorithm that performs well against simulations of realistic scenarios. We argue this new algorithm should be adopted by developers of Muon Scattering Tomography as an alternative to PoCA.
El control de las concentraciones empresariales en el sector electrico
NASA Astrophysics Data System (ADS)
Montoya Pardo, Milton Fernando
The rampant success of quantum theory is the result of applications of the 'new' quantum mechanics of Schrodinger and Heisenberg (1926-7), the Feynman-Schwinger-Tomonaga Quantum Electro-dynamics (1946-51), the electro-weak theory of Salaam, Weinberg, and Glashow (1967-9), and Quantum Chromodynamics (1973-); in fact, this success of 'the' quantum theory has depended on a continuous stream of brilliant and quite disparate mathematical formulations. In this carefully concealed ferment there lie plenty of unresolved difficulties, simply because in churning out fabulously accurate calculational tools there has been no sensible explanation of all that is going on. It is even argued that such an understanding is nothing to do with physics. A long-standing and famous illustration of this is the paradoxical thought-experiment of Einstein, Podolsky and Rosen (1935). Fundamental to all quantum theories, and also their paradoxes, is the location of sub-microscopic objects; or, rather, that the specification of such a location is fraught with mathematical inconsistency. This project encompasses a detailed, critical survey of the tangled history of Position within quantum theories. The first step is to show that, contrary to appearances, canonical quantum mechanics has only a vague notion of locality. After analysing a number of previous attempts at a 'relativistic quantum mechanics', two lines of thought are considered in detail. The first is the work of Wan and students, which is shown to be no real improvement on the iisu.al 'nonrelativistic' theory. The second is based on an idea of Dirac's - using backwards-in-time light-cones as the hypersurface in space-time. There remain considerable difficulties in the way of producing a consistent scheme here. To keep things nicely stirred up, the author then proposes his own approach - an adaptation of Feynman's QED propagators. This new approach is distinguished from Feynman's since the propagator or Green's function is not obtained by Feynman's rule. The type of equation solved is also different: instead of an initial-value problem, a solution that obeys a time-symmetric causality criterion is found for an inhomogeneous partial differential equation with homogeneous boundary conditions. To make the consideration of locality more precise, some results of Fourier transform theory are presented in a form that is directly applicable. Somewhat away from the main thrust of the thesis, there is also an attempt to explain, the manner in which quantum effects disappear as the number of particles increases in such things as experimental realisations of the EPR and de Broglie thought experiments.
Tectonica activa y geodinamica en el norte de centroamerica
NASA Astrophysics Data System (ADS)
Alvarez Gomez, Jose Antonio
The rampant success of quantum theory is the result of applications of the 'new' quantum mechanics of Schrodinger and Heisenberg (1926-7), the Feynman-Schwinger-Tomonaga Quantum Electro-dynamics (1946-51), the electro-weak theory of Salaam, Weinberg, and Glashow (1967-9), and Quantum Chromodynamics (1973-); in fact, this success of 'the' quantum theory has depended on a continuous stream of brilliant and quite disparate mathematical formulations. In this carefully concealed ferment there lie plenty of unresolved difficulties, simply because in churning out fabulously accurate calculational tools there has been no sensible explanation of all that is going on. It is even argued that such an understanding is nothing to do with physics. A long-standing and famous illustration of this is the paradoxical thought-experiment of Einstein, Podolsky and Rosen (1935). Fundamental to all quantum theories, and also their paradoxes, is the location of sub-microscopic objects; or, rather, that the specification of such a location is fraught with mathematical inconsistency. This project encompasses a detailed, critical survey of the tangled history of Position within quantum theories. The first step is to show that, contrary to appearances, canonical quantum mechanics has only a vague notion of locality. After analysing a number of previous attempts at a 'relativistic quantum mechanics', two lines of thought are considered in detail. The first is the work of Wan and students, which is shown to be no real improvement on the iisu.al 'nonrelativistic' theory. The second is based on an idea of Dirac's - using backwards-in-time light-cones as the hypersurface in space-time. There remain considerable difficulties in the way of producing a consistent scheme here. To keep things nicely stirred up, the author then proposes his own approach - an adaptation of Feynman's QED propagators. This new approach is distinguished from Feynman's since the propagator or Green's function is not obtained by Feynman's rule. The type of equation solved is also different: instead of an initial-value problem, a solution that obeys a time-symmetric causality criterion is found for an inhomogeneous partial differential equation with homogeneous boundary conditions. To make the consideration of locality more precise, some results of Fourier transform theory are presented in a form that is directly applicable. Somewhat away from the main thrust of the thesis, there is also an attempt to explain, the manner in which quantum effects disappear as the number of particles increases in such things as experimental realisations of the EPR and de Broglie thought experiments.
Estabilidad de ciertas ondas solitarias sometidas a perturbaciones estocasticas
NASA Astrophysics Data System (ADS)
Rodriguez Plaza, Maria Jesus
The rampant success of quantum theory is the result of applications of the 'new' quantum mechanics of Schrodinger and Heisenberg (1926-7), the Feynman-Schwinger-Tomonaga Quantum Electro-dynamics (1946-51), the electro-weak theory of Salaam, Weinberg, and Glashow (1967-9), and Quantum Chromodynamics (1973-); in fact, this success of 'the' quantum theory has depended on a continuous stream of brilliant and quite disparate mathematical formulations. In this carefully concealed ferment there lie plenty of unresolved difficulties, simply because in churning out fabulously accurate calculational tools there has been no sensible explanation of all that is going on. It is even argued that such an understanding is nothing to do with physics. A long-standing and famous illustration of this is the paradoxical thought-experiment of Einstein, Podolsky and Rosen (1935). Fundamental to all quantum theories, and also their paradoxes, is the location of sub-microscopic objects; or, rather, that the specification of such a location is fraught with mathematical inconsistency. This project encompasses a detailed, critical survey of the tangled history of Position within quantum theories. The first step is to show that, contrary to appearances, canonical quantum mechanics has only a vague notion of locality. After analysing a number of previous attempts at a 'relativistic quantum mechanics', two lines of thought are considered in detail. The first is the work of Wan and students, which is shown to be no real improvement on the iisu.al 'nonrelativistic' theory. The second is based on an idea of Dirac's - using backwards-in-time light-cones as the hypersurface in space-time. There remain considerable difficulties in the way of producing a consistent scheme here. To keep things nicely stirred up, the author then proposes his own approach - an adaptation of Feynman's QED propagators. This new approach is distinguished from Feynman's since the propagator or Green's function is not obtained by Feynman's rule. The type of equation solved is also different: instead of an initial-value problem, a solution that obeys a time-symmetric causality criterion is found for an inhomogeneous partial differential equation with homogeneous boundary conditions. To make the consideration of locality more precise, some results of Fourier transform theory are presented in a form that is directly applicable. Somewhat away from the main thrust of the thesis, there is also an attempt to explain, the manner in which quantum effects disappear as the number of particles increases in such things as experimental realisations of the EPR and de Broglie thought experiments.
The pursuit of locality in quantum mechanics
NASA Astrophysics Data System (ADS)
Hodkin, Malcolm
The rampant success of quantum theory is the result of applications of the 'new' quantum mechanics of Schrodinger and Heisenberg (1926-7), the Feynman-Schwinger-Tomonaga Quantum Electro-dynamics (1946-51), the electro-weak theory of Salaam, Weinberg, and Glashow (1967-9), and Quantum Chromodynamics (1973-); in fact, this success of 'the' quantum theory has depended on a continuous stream of brilliant and quite disparate mathematical formulations. In this carefully concealed ferment there lie plenty of unresolved difficulties, simply because in churning out fabulously accurate calculational tools there has been no sensible explanation of all that is going on. It is even argued that such an understanding is nothing to do with physics. A long-standing and famous illustration of this is the paradoxical thought-experiment of Einstein, Podolsky and Rosen (1935). Fundamental to all quantum theories, and also their paradoxes, is the location of sub-microscopic objects; or, rather, that the specification of such a location is fraught with mathematical inconsistency. This project encompasses a detailed, critical survey of the tangled history of Position within quantum theories. The first step is to show that, contrary to appearances, canonical quantum mechanics has only a vague notion of locality. After analysing a number of previous attempts at a 'relativistic quantum mechanics', two lines of thought are considered in detail. The first is the work of Wan and students, which is shown to be no real improvement on the iisu.al 'nonrelativistic' theory. The second is based on an idea of Dirac's - using backwards-in-time light-cones as the hypersurface in space-time. There remain considerable difficulties in the way of producing a consistent scheme here. To keep things nicely stirred up, the author then proposes his own approach - an adaptation of Feynman's QED propagators. This new approach is distinguished from Feynman's since the propagator or Green's function is not obtained by Feynman's rule. The type of equation solved is also different: instead of an initial-value problem, a solution that obeys a time-symmetric causality criterion is found for an inhomogeneous partial differential equation with homogeneous boundary conditions. To make the consideration of locality more precise, some results of Fourier transform theory are presented in a form that is directly applicable. Somewhat away from the main thrust of the thesis, there is also an attempt to explain, the manner in which quantum effects disappear as the number of particles increases in such things as experimental realisations of the EPR and de Broglie thought experiments.
NASA Astrophysics Data System (ADS)
Malpica Velasco, Jose Antonio
The rampant success of quantum theory is the result of applications of the 'new' quantum mechanics of Schrodinger and Heisenberg (1926-7), the Feynman-Schwinger-Tomonaga Quantum Electro-dynamics (1946-51), the electro-weak theory of Salaam, Weinberg, and Glashow (1967-9), and Quantum Chromodynamics (1973-); in fact, this success of 'the' quantum theory has depended on a continuous stream of brilliant and quite disparate mathematical formulations. In this carefully concealed ferment there lie plenty of unresolved difficulties, simply because in churning out fabulously accurate calculational tools there has been no sensible explanation of all that is going on. It is even argued that such an understanding is nothing to do with physics. A long-standing and famous illustration of this is the paradoxical thought-experiment of Einstein, Podolsky and Rosen (1935). Fundamental to all quantum theories, and also their paradoxes, is the location of sub-microscopic objects; or, rather, that the specification of such a location is fraught with mathematical inconsistency. This project encompasses a detailed, critical survey of the tangled history of Position within quantum theories. The first step is to show that, contrary to appearances, canonical quantum mechanics has only a vague notion of locality. After analysing a number of previous attempts at a 'relativistic quantum mechanics', two lines of thought are considered in detail. The first is the work of Wan and students, which is shown to be no real improvement on the iisu.al 'nonrelativistic' theory. The second is based on an idea of Dirac's - using backwards-in-time light-cones as the hypersurface in space-time. There remain considerable difficulties in the way of producing a consistent scheme here. To keep things nicely stirred up, the author then proposes his own approach - an adaptation of Feynman's QED propagators. This new approach is distinguished from Feynman's since the propagator or Green's function is not obtained by Feynman's rule. The type of equation solved is also different: instead of an initial-value problem, a solution that obeys a time-symmetric causality criterion is found for an inhomogeneous partial differential equation with homogeneous boundary conditions. To make the consideration of locality more precise, some results of Fourier transform theory are presented in a form that is directly applicable. Somewhat away from the main thrust of the thesis, there is also an attempt to explain, the manner in which quantum effects disappear as the number of particles increases in such things as experimental realisations of the EPR and de Broglie thought experiments.
Analisis espectroscopico de estrellas variables Delta Scuti
NASA Astrophysics Data System (ADS)
Solano Marquez, Enrique
The rampant success of quantum theory is the result of applications of the 'new' quantum mechanics of Schrodinger and Heisenberg (1926-7), the Feynman-Schwinger-Tomonaga Quantum Electro-dynamics (1946-51), the electro-weak theory of Salaam, Weinberg, and Glashow (1967-9), and Quantum Chromodynamics (1973-); in fact, this success of 'the' quantum theory has depended on a continuous stream of brilliant and quite disparate mathematical formulations. In this carefully concealed ferment there lie plenty of unresolved difficulties, simply because in churning out fabulously accurate calculational tools there has been no sensible explanation of all that is going on. It is even argued that such an understanding is nothing to do with physics. A long-standing and famous illustration of this is the paradoxical thought-experiment of Einstein, Podolsky and Rosen (1935). Fundamental to all quantum theories, and also their paradoxes, is the location of sub-microscopic objects; or, rather, that the specification of such a location is fraught with mathematical inconsistency. This project encompasses a detailed, critical survey of the tangled history of Position within quantum theories. The first step is to show that, contrary to appearances, canonical quantum mechanics has only a vague notion of locality. After analysing a number of previous attempts at a 'relativistic quantum mechanics', two lines of thought are considered in detail. The first is the work of Wan and students, which is shown to be no real improvement on the iisu.al 'nonrelativistic' theory. The second is based on an idea of Dirac's - using backwards-in-time light-cones as the hypersurface in space-time. There remain considerable difficulties in the way of producing a consistent scheme here. To keep things nicely stirred up, the author then proposes his own approach - an adaptation of Feynman's QED propagators. This new approach is distinguished from Feynman's since the propagator or Green's function is not obtained by Feynman's rule. The type of equation solved is also different: instead of an initial-value problem, a solution that obeys a time-symmetric causality criterion is found for an inhomogeneous partial differential equation with homogeneous boundary conditions. To make the consideration of locality more precise, some results of Fourier transform theory are presented in a form that is directly applicable. Somewhat away from the main thrust of the thesis, there is also an attempt to explain, the manner in which quantum effects disappear as the number of particles increases in such things as experimental realisations of the EPR and de Broglie thought experiments.
Inversion gravimetrica 3D por tecnicas de evolucion: Aplicacion a la Isla de Fuerteventura
NASA Astrophysics Data System (ADS)
Gonzalez Montesinos, Fuensanta
The rampant success of quantum theory is the result of applications of the 'new' quantum mechanics of Schrodinger and Heisenberg (1926-7), the Feynman-Schwinger-Tomonaga Quantum Electro-dynamics (1946-51), the electro-weak theory of Salaam, Weinberg, and Glashow (1967-9), and Quantum Chromodynamics (1973-); in fact, this success of 'the' quantum theory has depended on a continuous stream of brilliant and quite disparate mathematical formulations. In this carefully concealed ferment there lie plenty of unresolved difficulties, simply because in churning out fabulously accurate calculational tools there has been no sensible explanation of all that is going on. It is even argued that such an understanding is nothing to do with physics. A long-standing and famous illustration of this is the paradoxical thought-experiment of Einstein, Podolsky and Rosen (1935). Fundamental to all quantum theories, and also their paradoxes, is the location of sub-microscopic objects; or, rather, that the specification of such a location is fraught with mathematical inconsistency. This project encompasses a detailed, critical survey of the tangled history of Position within quantum theories. The first step is to show that, contrary to appearances, canonical quantum mechanics has only a vague notion of locality. After analysing a number of previous attempts at a 'relativistic quantum mechanics', two lines of thought are considered in detail. The first is the work of Wan and students, which is shown to be no real improvement on the iisu.al 'nonrelativistic' theory. The second is based on an idea of Dirac's - using backwards-in-time light-cones as the hypersurface in space-time. There remain considerable difficulties in the way of producing a consistent scheme here. To keep things nicely stirred up, the author then proposes his own approach - an adaptation of Feynman's QED propagators. This new approach is distinguished from Feynman's since the propagator or Green's function is not obtained by Feynman's rule. The type of equation solved is also different: instead of an initial-value problem, a solution that obeys a time-symmetric causality criterion is found for an inhomogeneous partial differential equation with homogeneous boundary conditions. To make the consideration of locality more precise, some results of Fourier transform theory are presented in a form that is directly applicable. Somewhat away from the main thrust of the thesis, there is also an attempt to explain, the manner in which quantum effects disappear as the number of particles increases in such things as experimental realisations of the EPR and de Broglie thought experiments.
Evolution tectonothermale du massif Hercynien des Rehamna (zone centre-mesetienne, Maroc)
NASA Astrophysics Data System (ADS)
Aghzer, Abdel Mouhsine
The rampant success of quantum theory is the result of applications of the 'new' quantum mechanics of Schrodinger and Heisenberg (1926-7), the Feynman-Schwinger-Tomonaga Quantum Electro-dynamics (1946-51), the electro-weak theory of Salaam, Weinberg, and Glashow (1967-9), and Quantum Chromodynamics (1973-); in fact, this success of 'the' quantum theory has depended on a continuous stream of brilliant and quite disparate mathematical formulations. In this carefully concealed ferment there lie plenty of unresolved difficulties, simply because in churning out fabulously accurate calculational tools there has been no sensible explanation of all that is going on. It is even argued that such an understanding is nothing to do with physics. A long-standing and famous illustration of this is the paradoxical thought-experiment of Einstein, Podolsky and Rosen (1935). Fundamental to all quantum theories, and also their paradoxes, is the location of sub-microscopic objects; or, rather, that the specification of such a location is fraught with mathematical inconsistency. This project encompasses a detailed, critical survey of the tangled history of Position within quantum theories. The first step is to show that, contrary to appearances, canonical quantum mechanics has only a vague notion of locality. After analysing a number of previous attempts at a 'relativistic quantum mechanics', two lines of thought are considered in detail. The first is the work of Wan and students, which is shown to be no real improvement on the iisu.al 'nonrelativistic' theory. The second is based on an idea of Dirac's - using backwards-in-time light-cones as the hypersurface in space-time. There remain considerable difficulties in the way of producing a consistent scheme here. To keep things nicely stirred up, the author then proposes his own approach - an adaptation of Feynman's QED propagators. This new approach is distinguished from Feynman's since the propagator or Green's function is not obtained by Feynman's rule. The type of equation solved is also different: instead of an initial-value problem, a solution that obeys a time-symmetric causality criterion is found for an inhomogeneous partial differential equation with homogeneous boundary conditions. To make the consideration of locality more precise, some results of Fourier transform theory are presented in a form that is directly applicable. Somewhat away from the main thrust of the thesis, there is also an attempt to explain, the manner in which quantum effects disappear as the number of particles increases in such things as experimental realisations of the EPR and de Broglie thought experiments.
NASA Astrophysics Data System (ADS)
Bejar Pizarro, Marta
The rampant success of quantum theory is the result of applications of the 'new' quantum mechanics of Schrodinger and Heisenberg (1926-7), the Feynman-Schwinger-Tomonaga Quantum Electro-dynamics (1946-51), the electro-weak theory of Salaam, Weinberg, and Glashow (1967-9), and Quantum Chromodynamics (1973-); in fact, this success of 'the' quantum theory has depended on a continuous stream of brilliant and quite disparate mathematical formulations. In this carefully concealed ferment there lie plenty of unresolved difficulties, simply because in churning out fabulously accurate calculational tools there has been no sensible explanation of all that is going on. It is even argued that such an understanding is nothing to do with physics. A long-standing and famous illustration of this is the paradoxical thought-experiment of Einstein, Podolsky and Rosen (1935). Fundamental to all quantum theories, and also their paradoxes, is the location of sub-microscopic objects; or, rather, that the specification of such a location is fraught with mathematical inconsistency. This project encompasses a detailed, critical survey of the tangled history of Position within quantum theories. The first step is to show that, contrary to appearances, canonical quantum mechanics has only a vague notion of locality. After analysing a number of previous attempts at a 'relativistic quantum mechanics', two lines of thought are considered in detail. The first is the work of Wan and students, which is shown to be no real improvement on the iisu.al 'nonrelativistic' theory. The second is based on an idea of Dirac's - using backwards-in-time light-cones as the hypersurface in space-time. There remain considerable difficulties in the way of producing a consistent scheme here. To keep things nicely stirred up, the author then proposes his own approach - an adaptation of Feynman's QED propagators. This new approach is distinguished from Feynman's since the propagator or Green's function is not obtained by Feynman's rule. The type of equation solved is also different: instead of an initial-value problem, a solution that obeys a time-symmetric causality criterion is found for an inhomogeneous partial differential equation with homogeneous boundary conditions. To make the consideration of locality more precise, some results of Fourier transform theory are presented in a form that is directly applicable. Somewhat away from the main thrust of the thesis, there is also an attempt to explain, the manner in which quantum effects disappear as the number of particles increases in such things as experimental realisations of the EPR and de Broglie thought experiments.
NASA Astrophysics Data System (ADS)
Fillali, Laila
The rampant success of quantum theory is the result of applications of the 'new' quantum mechanics of Schrodinger and Heisenberg (1926-7), the Feynman-Schwinger-Tomonaga Quantum Electro-dynamics (1946-51), the electro-weak theory of Salaam, Weinberg, and Glashow (1967-9), and Quantum Chromodynamics (1973-); in fact, this success of 'the' quantum theory has depended on a continuous stream of brilliant and quite disparate mathematical formulations. In this carefully concealed ferment there lie plenty of unresolved difficulties, simply because in churning out fabulously accurate calculational tools there has been no sensible explanation of all that is going on. It is even argued that such an understanding is nothing to do with physics. A long-standing and famous illustration of this is the paradoxical thought-experiment of Einstein, Podolsky and Rosen (1935). Fundamental to all quantum theories, and also their paradoxes, is the location of sub-microscopic objects; or, rather, that the specification of such a location is fraught with mathematical inconsistency. This project encompasses a detailed, critical survey of the tangled history of Position within quantum theories. The first step is to show that, contrary to appearances, canonical quantum mechanics has only a vague notion of locality. After analysing a number of previous attempts at a 'relativistic quantum mechanics', two lines of thought are considered in detail. The first is the work of Wan and students, which is shown to be no real improvement on the iisu.al 'nonrelativistic' theory. The second is based on an idea of Dirac's - using backwards-in-time light-cones as the hypersurface in space-time. There remain considerable difficulties in the way of producing a consistent scheme here. To keep things nicely stirred up, the author then proposes his own approach - an adaptation of Feynman's QED propagators. This new approach is distinguished from Feynman's since the propagator or Green's function is not obtained by Feynman's rule. The type of equation solved is also different: instead of an initial-value problem, a solution that obeys a time-symmetric causality criterion is found for an inhomogeneous partial differential equation with homogeneous boundary conditions. To make the consideration of locality more precise, some results of Fourier transform theory are presented in a form that is directly applicable. Somewhat away from the main thrust of the thesis, there is also an attempt to explain, the manner in which quantum effects disappear as the number of particles increases in such things as experimental realisations of the EPR and de Broglie thought experiments.
A Programmable Five Qubit Quantum Computer Using Trapped Atomic Ions
NASA Astrophysics Data System (ADS)
Debnath, Shantanu
Quantum computers can solve certain problems more efficiently compared to conventional classical methods. In the endeavor to build a quantum computer, several competing platforms have emerged that can implement certain quantum algorithms using a few qubits. However, the demonstrations so far have been done usually by tailoring the hardware to meet the requirements of a particular algorithm implemented for a limited number of instances. Although such proof of principal implementations are important to verify the working of algorithms on a physical system, they further need to have the potential to serve as a general purpose quantum computer allowing the flexibility required for running multiple algorithms and be scaled up to host more qubits. Here we demonstrate a small programmable quantum computer based on five trapped atomic ions each of which serves as a qubit. By optically resolving each ion we can individually address them in order to perform a complete set of single-qubit and fully connected two-qubit quantum gates and alsoperform efficient individual qubit measurements. We implement a computation architecture that accepts an algorithm from a user interface in the form of a standard logic gate sequence and decomposes it into fundamental quantum operations that are native to the hardware using a set of compilation instructions that are defined within the software. These operations are then effected through a pattern of laser pulses that perform coherent rotations on targeted qubits in the chain. The architecture implemented in the experiment therefore gives us unprecedented flexibility in the programming of any quantum algorithm while staying blind to the underlying hardware. As a demonstration we implement the Deutsch-Jozsa and Bernstein-Vazirani algorithms on the five-qubit processor and achieve average success rates of 95 and 90 percent, respectively. We also implement a five-qubit coherent quantum Fourier transform and examine its performance in the period finding and phase estimation protocol. We find fidelities of 84 and 62 percent, respectively. While maintaining the same computation architecture the system can be scaled to more ions using resources that scale favorably (O(N. 2)) with the numberof qubits N.
CPU-GPU hybrid accelerating the Zuker algorithm for RNA secondary structure prediction applications
2012-01-01
Background Prediction of ribonucleic acid (RNA) secondary structure remains one of the most important research areas in bioinformatics. The Zuker algorithm is one of the most popular methods of free energy minimization for RNA secondary structure prediction. Thus far, few studies have been reported on the acceleration of the Zuker algorithm on general-purpose processors or on extra accelerators such as Field Programmable Gate-Array (FPGA) and Graphics Processing Units (GPU). To the best of our knowledge, no implementation combines both CPU and extra accelerators, such as GPUs, to accelerate the Zuker algorithm applications. Results In this paper, a CPU-GPU hybrid computing system that accelerates Zuker algorithm applications for RNA secondary structure prediction is proposed. The computing tasks are allocated between CPU and GPU for parallel cooperate execution. Performance differences between the CPU and the GPU in the task-allocation scheme are considered to obtain workload balance. To improve the hybrid system performance, the Zuker algorithm is optimally implemented with special methods for CPU and GPU architecture. Conclusions Speedup of 15.93× over optimized multi-core SIMD CPU implementation and performance advantage of 16% over optimized GPU implementation are shown in the experimental results. More than 14% of the sequences are executed on CPU in the hybrid system. The system combining CPU and GPU to accelerate the Zuker algorithm is proven to be promising and can be applied to other bioinformatics applications. PMID:22369626
Development of Algorithms for Control of Humidity in Plant Growth Chambers
NASA Technical Reports Server (NTRS)
Costello, Thomas A.
2003-01-01
Algorithms were developed to control humidity in plant growth chambers used for research on bioregenerative life support at Kennedy Space Center. The algorithms used the computed water vapor pressure (based on measured air temperature and relative humidity) as the process variable, with time-proportioned outputs to operate the humidifier and de-humidifier. Algorithms were based upon proportional-integral-differential (PID) and Fuzzy Logic schemes and were implemented using I/O Control software (OPTO-22) to define and download the control logic to an autonomous programmable logic controller (PLC, ultimate ethernet brain and assorted input-output modules, OPTO-22), which performed the monitoring and control logic processing, as well the physical control of the devices that effected the targeted environment in the chamber. During limited testing, the PLC's successfully implemented the intended control schemes and attained a control resolution for humidity of less than 1%. The algorithms have potential to be used not only with autonomous PLC's but could also be implemented within network-based supervisory control programs. This report documents unique control features that were implemented within the OPTO-22 framework and makes recommendations regarding future uses of the hardware and software for biological research by NASA.
eqMAXEL: A new automatic earthquake location algorithm implementation for Earthworm
NASA Astrophysics Data System (ADS)
Lisowski, S.; Friberg, P. A.; Sheen, D. H.
2017-12-01
A common problem with automated earthquake location systems for a local to regional scale seismic network is false triggering and false locations inside the network caused by larger regional to teleseismic distance earthquakes. This false location issue also presents a problem for earthquake early warning systems where societal impacts of false alarms can be very expensive. Towards solving this issue, Sheen et al. (2016) implemented a robust maximum-likelihood earthquake location algorithm known as MAXEL. It was shown with both synthetics and real-data for a small number of arrivals, that large regional events were easily identifiable through metrics in the MAXEL algorithm. In the summer of 2017, we collaboratively implemented the MAXEL algorithm into a fully functional Earthworm module and tested it in regions of the USA where false detections and alarming are observed. We show robust improvement in the ability of the Earthworm system to filter out regional and teleseismic events that would have falsely located inside the network using the traditional Earthworm hypoinverse solution. We also explore using different grid sizes in the implementation of the MAXEL algorithm, which was originally designed with South Korea as the target network size.
NASA Astrophysics Data System (ADS)
Howerton, William
This thesis presents a method for the integration of complex network control algorithms with localized agent specific algorithms for maneuvering and obstacle avoidance. This method allows for successful implementation of group and agent specific behaviors. It has proven to be robust and will work for a variety of vehicle platforms. Initially, a review and implementation of two specific algorithms will be detailed. The first, a modified Kuramoto model was developed by Xu [1] which utilizes tools from graph theory to efficiently perform the task of distributing agents. The second algorithm developed by Kim [2] is an effective method for wheeled robots to avoid local obstacles using a limit-cycle navigation method. The results of implementing these methods on a test-bed of wheeled robots will be presented. Control issues related to outside disturbances not anticipated in the original theory are then discussed. A novel method of using simulated agents to separate the task of distributing agents from agent specific velocity and heading commands has been developed and implemented to address these issues. This new method can be used to combine various behaviors and is not limited to a specific control algorithm.
Seamless Merging of Hypertext and Algorithm Animation
ERIC Educational Resources Information Center
Karavirta, Ville
2009-01-01
Online learning material that students use by themselves is one of the typical usages of algorithm animation (AA). Thus, the integration of algorithm animations into hypertext is seen as an important topic today to promote the usage of algorithm animation in teaching. This article presents an algorithm animation viewer implemented purely using…
NASA Technical Reports Server (NTRS)
Schoenwald, Adam J.; Bradley, Damon C.; Mohammed, Priscilla N.; Piepmeier, Jeffrey R.; Wong, Mark
2016-01-01
Radio-frequency interference (RFI) is a known problem for passive remote sensing as evidenced in the L-band radiometers SMOS, Aquarius and more recently, SMAP. Various algorithms have been developed and implemented on SMAP to improve science measurements. This was achieved by the use of a digital microwave radiometer. RFI mitigation becomes more challenging for microwave radiometers operating at higher frequencies in shared allocations. At higher frequencies larger bandwidths are also desirable for lower measurement noise further adding to processing challenges. This work focuses on finding improved RFI mitigation techniques that will be effective at additional frequencies and at higher bandwidths. To aid the development and testing of applicable detection and mitigation techniques, a wide-band RFI algorithm testing environment has been developed using the Reconfigurable Open Architecture Computing Hardware System (ROACH) built by the Collaboration for Astronomy Signal Processing and Electronics Research (CASPER) Group. The testing environment also consists of various test equipment used to reproduce typical signals that a radiometer may see including those with and without RFI. The testing environment permits quick evaluations of RFI mitigation algorithms as well as show that they are implementable in hardware. The algorithm implemented is a complex signal kurtosis detector which was modeled and simulated. The complex signal kurtosis detector showed improved performance over the real kurtosis detector under certain conditions. The real kurtosis is implemented on SMAP at 24 MHz bandwidth. The complex signal kurtosis algorithm was then implemented in hardware at 200 MHz bandwidth using the ROACH. In this work, performance of the complex signal kurtosis and the real signal kurtosis are compared. Performance evaluations and comparisons in both simulation as well as experimental hardware implementations were done with the use of receiver operating characteristic (ROC) curves. The complex kurtosis algorithm has the potential to reduce data rate due to onboard processing in addition to improving RFI detection performance.
Implementation of LSCMA adaptive array terminal for mobile satellite communications
NASA Astrophysics Data System (ADS)
Zhou, Shun; Wang, Huali; Xu, Zhijun
2007-11-01
This paper considers the application of adaptive array antenna based on the least squares constant modulus algorithm (LSCMA) for interference rejection in mobile SATCOM terminals. A two-element adaptive array scheme is implemented with a combination of ADI TS201S DSP chips and Altera Stratix II FPGA device, which makes a cooperating computation for adaptive beamforming. Its interference suppressing performance is verified via Matlab simulations. Digital hardware system is implemented to execute the operations of LSCMA beamforming algorithm that is represented by an algorithm flowchart. The result of simulations and test indicate that this scheme can improve the anti-jamming performance of terminals.
FPGA implementation of ICA algorithm for blind signal separation and adaptive noise canceling.
Kim, Chang-Min; Park, Hyung-Min; Kim, Taesu; Choi, Yoon-Kyung; Lee, Soo-Young
2003-01-01
An field programmable gate array (FPGA) implementation of independent component analysis (ICA) algorithm is reported for blind signal separation (BSS) and adaptive noise canceling (ANC) in real time. In order to provide enormous computing power for ICA-based algorithms with multipath reverberation, a special digital processor is designed and implemented in FPGA. The chip design fully utilizes modular concept and several chips may be put together for complex applications with a large number of noise sources. Experimental results with a fabricated test board are reported for ANC only, BSS only, and simultaneous ANC/BSS, which demonstrates successful speech enhancement in real environments in real time.
Rhoads, Daniel D; Genzen, Jonathan R; Bashleben, Christine P; Faix, James D; Ansari, M Qasim
2017-01-01
-Syphilis serology screening in laboratory practice is evolving. Traditionally, the syphilis screening algorithm begins with a nontreponemal immunoassay, which is manually performed by a laboratory technologist. In contrast, the reverse algorithm begins with a treponemal immunoassay, which can be automated. The Centers for Disease Control and Prevention has recognized both approaches, but little is known about the current state of laboratory practice, which could impact test utilization and interpretation. -To assess the current state of laboratory practice for syphilis serologic screening. -In August 2015, a voluntary questionnaire was sent to the 2360 laboratories that subscribe to the College of American Pathologists syphilis serology proficiency survey. -Of the laboratories surveyed, 98% (2316 of 2360) returned the questionnaire, and about 83% (1911 of 2316) responded to at least some questions. Twenty-eight percent (378 of 1364) reported revision of their syphilis screening algorithm within the past 2 years, and 9% (170 of 1905) of laboratories anticipated changing their screening algorithm in the coming year. Sixty-three percent (1205 of 1911) reported using the traditional algorithm, 16% (304 of 1911) reported using the reverse algorithm, and 2.5% (47 of 1911) reported using both algorithms, whereas 9% (169 of 1911) reported not performing a reflex confirmation test. Of those performing the reverse algorithm, 74% (282 of 380) implemented a new testing platform when introducing the new algorithm. -The majority of laboratories still perform the traditional algorithm, but a significant minority have implemented the reverse-screening algorithm. Although the nontreponemal immunologic response typically wanes after cure and becomes undetectable, treponemal immunoassays typically remain positive for life, and it is important for laboratorians and clinicians to consider these assay differences when implementing, using, and interpreting serologic syphilis screening algorithms.
Ultrafast adiabatic quantum algorithm for the NP-complete exact cover problem
Wang, Hefeng; Wu, Lian-Ao
2016-01-01
An adiabatic quantum algorithm may lose quantumness such as quantum coherence entirely in its long runtime, and consequently the expected quantum speedup of the algorithm does not show up. Here we present a general ultrafast adiabatic quantum algorithm. We show that by applying a sequence of fast random or regular signals during evolution, the runtime can be reduced substantially, whereas advantages of the adiabatic algorithm remain intact. We also propose a randomized Trotter formula and show that the driving Hamiltonian and the proposed sequence of fast signals can be implemented simultaneously. We illustrate the algorithm by solving the NP-complete 3-bit exact cover problem (EC3), where NP stands for nondeterministic polynomial time, and put forward an approach to implementing the problem with trapped ions. PMID:26923834
Ho, ThienLuan; Oh, Seung-Rohk
2017-01-01
Approximate string matching with k-differences has a number of practical applications, ranging from pattern recognition to computational biology. This paper proposes an efficient memory-access algorithm for parallel approximate string matching with k-differences on Graphics Processing Units (GPUs). In the proposed algorithm, all threads in the same GPUs warp share data using warp-shuffle operation instead of accessing the shared memory. Moreover, we implement the proposed algorithm by exploiting the memory structure of GPUs to optimize its performance. Experiment results for real DNA packages revealed that the performance of the proposed algorithm and its implementation archived up to 122.64 and 1.53 times compared to that of sequential algorithm on CPU and previous parallel approximate string matching algorithm on GPUs, respectively. PMID:29016700
NASA Astrophysics Data System (ADS)
Liu, Zhi; Zhou, Baotong; Zhang, Changnian
2017-03-01
Vehicle-mounted panoramic system is important safety assistant equipment for driving. However, traditional systems only render fixed top-down perspective view of limited view field, which may have potential safety hazard. In this paper, a texture mapping algorithm for 3D vehicle-mounted panoramic system is introduced, and an implementation of the algorithm utilizing OpenGL ES library based on Android smart platform is presented. Initial experiment results show that the proposed algorithm can render a good 3D panorama, and has the ability to change view point freely.
A Circuit-Based Quantum Algorithm Driven by Transverse Fields for Grover's Problem
NASA Technical Reports Server (NTRS)
Jiang, Zhang; Rieffel, Eleanor G.; Wang, Zhihui
2017-01-01
We designed a quantum search algorithm, giving the same quadratic speedup achieved by Grover's original algorithm; we replace Grover's diffusion operator (hard to implement) with a product diffusion operator generated by transverse fields (easy to implement). In our algorithm, the problem Hamiltonian (oracle) and the transverse fields are applied to the system alternatively. We construct such a sequence that the corresponding unitary generates a closed transition between the initial state (even superposition of all states) and a modified target state, which has a high degree of overlap with the original target state.
Implementing a GPU-based numerical algorithm for modelling dynamics of a high-speed train
NASA Astrophysics Data System (ADS)
Sytov, E. S.; Bratus, A. S.; Yurchenko, D.
2018-04-01
This paper discusses the initiative of implementing a GPU-based numerical algorithm for studying various phenomena associated with dynamics of a high-speed railway transport. The proposed numerical algorithm for calculating a critical speed of the bogie is based on the first Lyapunov number. Numerical algorithm is validated by analytical results, derived for a simple model. A dynamic model of a carriage connected to a new dual-wheelset flexible bogie is studied for linear and dry friction damping. Numerical results obtained by CPU, MPU and GPU approaches are compared and appropriateness of these methods is discussed.
Implementing Linear Algebra Related Algorithms on the TI-92+ Calculator.
ERIC Educational Resources Information Center
Alexopoulos, John; Abraham, Paul
2001-01-01
Demonstrates a less utilized feature of the TI-92+: its natural and powerful programming language. Shows how to implement several linear algebra related algorithms including the Gram-Schmidt process, Least Squares Approximations, Wronskians, Cholesky Decompositions, and Generalized Linear Least Square Approximations with QR Decompositions.…
Preliminary Study of Image Reconstruction Algorithm on a Digital Signal Processor
2014-03-01
5.2 Comparison of CPU-GPU, CPU-FPGA, and CPU-DSP Designs The work for implementing VHDL description of the back-projection algorithm on a physical...FPGA was not complete. Hence, the DSP implementation results are compared with the simulated results for the VHDL design. Simulating VHDL provides an...rather than at the software level. Depending on an application’s characteristics, FPGA implementations can provide a significant performance
Comparison and analysis of nonlinear algorithms for compressed sensing in MRI.
Yu, Yeyang; Hong, Mingjian; Liu, Feng; Wang, Hua; Crozier, Stuart
2010-01-01
Compressed sensing (CS) theory has been recently applied in Magnetic Resonance Imaging (MRI) to accelerate the overall imaging process. In the CS implementation, various algorithms have been used to solve the nonlinear equation system for better image quality and reconstruction speed. However, there are no explicit criteria for an optimal CS algorithm selection in the practical MRI application. A systematic and comparative study of those commonly used algorithms is therefore essential for the implementation of CS in MRI. In this work, three typical algorithms, namely, the Gradient Projection For Sparse Reconstruction (GPSR) algorithm, Interior-point algorithm (l(1)_ls), and the Stagewise Orthogonal Matching Pursuit (StOMP) algorithm are compared and investigated in three different imaging scenarios, brain, angiogram and phantom imaging. The algorithms' performances are characterized in terms of image quality and reconstruction speed. The theoretical results show that the performance of the CS algorithms is case sensitive; overall, the StOMP algorithm offers the best solution in imaging quality, while the GPSR algorithm is the most efficient one among the three methods. In the next step, the algorithm performances and characteristics will be experimentally explored. It is hoped that this research will further support the applications of CS in MRI.
An Efficient Randomized Algorithm for Real-Time Process Scheduling in PicOS Operating System
NASA Astrophysics Data System (ADS)
Helmy*, Tarek; Fatai, Anifowose; Sallam, El-Sayed
PicOS is an event-driven operating environment designed for use with embedded networked sensors. More specifically, it is designed to support the concurrency in intensive operations required by networked sensors with minimal hardware requirements. Existing process scheduling algorithms of PicOS; a commercial tiny, low-footprint, real-time operating system; have their associated drawbacks. An efficient, alternative algorithm, based on a randomized selection policy, has been proposed, demonstrated, confirmed for efficiency and fairness, on the average, and has been recommended for implementation in PicOS. Simulations were carried out and performance measures such as Average Waiting Time (AWT) and Average Turn-around Time (ATT) were used to assess the efficiency of the proposed randomized version over the existing ones. The results prove that Randomized algorithm is the best and most attractive for implementation in PicOS, since it is most fair and has the least AWT and ATT on average over the other non-preemptive scheduling algorithms implemented in this paper.
A high speed implementation of the random decrement algorithm
NASA Technical Reports Server (NTRS)
Kiraly, L. J.
1982-01-01
The algorithm is useful for measuring net system damping levels in stochastic processes and for the development of equivalent linearized system response models. The algorithm works by summing together all subrecords which occur after predefined threshold level is crossed. The random decrement signature is normally developed by scanning stored data and adding subrecords together. The high speed implementation of the random decrement algorithm exploits the digital character of sampled data and uses fixed record lengths of 2(n) samples to greatly speed up the process. The contributions to the random decrement signature of each data point was calculated only once and in the same sequence as the data were taken. A hardware implementation of the algorithm using random logic is diagrammed and the process is shown to be limited only by the record size and the threshold crossing frequency of the sampled data. With a hardware cycle time of 200 ns and 1024 point signature, a threshold crossing frequency of 5000 Hertz can be processed and a stably averaged signature presented in real time.
Algorithm architecture co-design for ultra low-power image sensor
NASA Astrophysics Data System (ADS)
Laforest, T.; Dupret, A.; Verdant, A.; Lattard, D.; Villard, P.
2012-03-01
In a context of embedded video surveillance, stand alone leftbehind image sensors are used to detect events with high level of confidence, but also with a very low power consumption. Using a steady camera, motion detection algorithms based on background estimation to find regions in movement are simple to implement and computationally efficient. To reduce power consumption, the background is estimated using a down sampled image formed of macropixels. In order to extend the class of moving objects to be detected, we propose an original mixed mode architecture developed thanks to an algorithm architecture co-design methodology. This programmable architecture is composed of a vector of SIMD processors. A basic RISC architecture was optimized in order to implement motion detection algorithms with a dedicated set of 42 instructions. Definition of delta modulation as a calculation primitive has allowed to implement algorithms in a very compact way. Thereby, a 1920x1080@25fps CMOS image sensor performing integrated motion detection is proposed with a power estimation of 1.8 mW.
A Tensor Product Formulation of Strassen's Matrix Multiplication Algorithm with Memory Reduction
Kumar, B.; Huang, C. -H.; Sadayappan, P.; ...
1995-01-01
In this article, we present a program generation strategy of Strassen's matrix multiplication algorithm using a programming methodology based on tensor product formulas. In this methodology, block recursive programs such as the fast Fourier Transforms and Strassen's matrix multiplication algorithm are expressed as algebraic formulas involving tensor products and other matrix operations. Such formulas can be systematically translated to high-performance parallel/vector codes for various architectures. In this article, we present a nonrecursive implementation of Strassen's algorithm for shared memory vector processors such as the Cray Y-MP. A previous implementation of Strassen's algorithm synthesized from tensor product formulas required working storagemore » of size O(7 n ) for multiplying 2 n × 2 n matrices. We present a modified formulation in which the working storage requirement is reduced to O(4 n ). The modified formulation exhibits sufficient parallelism for efficient implementation on a shared memory multiprocessor. Performance results on a Cray Y-MP8/64 are presented.« less
A novel pipeline based FPGA implementation of a genetic algorithm
NASA Astrophysics Data System (ADS)
Thirer, Nonel
2014-05-01
To solve problems when an analytical solution is not available, more and more bio-inspired computation techniques have been applied in the last years. Thus, an efficient algorithm is the Genetic Algorithm (GA), which imitates the biological evolution process, finding the solution by the mechanism of "natural selection", where the strong has higher chances to survive. A genetic algorithm is an iterative procedure which operates on a population of individuals called "chromosomes" or "possible solutions" (usually represented by a binary code). GA performs several processes with the population individuals to produce a new population, like in the biological evolution. To provide a high speed solution, pipelined based FPGA hardware implementations are used, with a nstages pipeline for a n-phases genetic algorithm. The FPGA pipeline implementations are constraints by the different execution time of each stage and by the FPGA chip resources. To minimize these difficulties, we propose a bio-inspired technique to modify the crossover step by using non identical twins. Thus two of the chosen chromosomes (parents) will build up two new chromosomes (children) not only one as in classical GA. We analyze the contribution of this method to reduce the execution time in the asynchronous and synchronous pipelines and also the possibility to a cheaper FPGA implementation, by using smaller populations. The full hardware architecture for a FPGA implementation to our target ALTERA development card is presented and analyzed.
The Design and Implementation of Indoor Localization System Using Magnetic Field Based on Smartphone
NASA Astrophysics Data System (ADS)
Liu, J.; Jiang, C.; Shi, Z.
2017-09-01
Sufficient signal nodes are mostly required to implement indoor localization in mainstream research. Magnetic field take advantage of high precision, stable and reliability, and the reception of magnetic field signals is reliable and uncomplicated, it could be realized by geomagnetic sensor on smartphone, without external device. After the study of indoor positioning technologies, choose the geomagnetic field data as fingerprints to design an indoor localization system based on smartphone. A localization algorithm that appropriate geomagnetic matching is designed, and present filtering algorithm and algorithm for coordinate conversion. With the implement of plot geomagnetic fingerprints, the indoor positioning of smartphone without depending on external devices can be achieved. Finally, an indoor positioning system which is based on Android platform is successfully designed, through the experiments, proved the capability and effectiveness of indoor localization algorithm.
Method for implementation of recursive hierarchical segmentation on parallel computers
NASA Technical Reports Server (NTRS)
Tilton, James C. (Inventor)
2005-01-01
A method, computer readable storage, and apparatus for implementing a recursive hierarchical segmentation algorithm on a parallel computing platform. The method includes setting a bottom level of recursion that defines where a recursive division of an image into sections stops dividing, and setting an intermediate level of recursion where the recursive division changes from a parallel implementation into a serial implementation. The segmentation algorithm is implemented according to the set levels. The method can also include setting a convergence check level of recursion with which the first level of recursion communicates with when performing a convergence check.
Simulating large atmospheric phase screens using a woofer-tweeter algorithm.
Buscher, David F
2016-10-03
We describe an algorithm for simulating atmospheric wavefront perturbations over ranges of spatial and temporal scales spanning more than 4 orders of magnitude. An open-source implementation of the algorithm written in Python can simulate the evolution of the perturbations more than an order-of-magnitude faster than real time. Testing of the implementation using metrics appropriate to adaptive optics systems and long-baseline interferometers show accuracies at the few percent level or better.
Comparison of the MPP with other supercomputers for LANDSAT data processing
NASA Technical Reports Server (NTRS)
Ozga, Martin
1987-01-01
The massively parallel processor is compared to the CRAY X-MP and the CYBER-205 for LANDSAT data processing. The maximum likelihood classification algorithm is the basis for comparison since this algorithm is simple to implement and vectorizes very well. The algorithm was implemented on all three machines and tested by classifying the same full scene of LANDSAT multispectral scan data. Timings are compared as well as features of the machines and available software.
Massively Parallel Solution of Poisson Equation on Coarse Grain MIMD Architectures
NASA Technical Reports Server (NTRS)
Fijany, A.; Weinberger, D.; Roosta, R.; Gulati, S.
1998-01-01
In this paper a new algorithm, designated as Fast Invariant Imbedding algorithm, for solution of Poisson equation on vector and massively parallel MIMD architectures is presented. This algorithm achieves the same optimal computational efficiency as other Fast Poisson solvers while offering a much better structure for vector and parallel implementation. Our implementation on the Intel Delta and Paragon shows that a speedup of over two orders of magnitude can be achieved even for moderate size problems.
Implementation of a Multi-Robot Coverage Algorithm on a Two-Dimensional, Grid-Based Environment
2017-06-01
two planar laser range finders with a 180-degree field of view , color camera, vision beacons, and wireless communicator. In their system, the robots...Master’s thesis 4. TITLE AND SUBTITLE IMPLEMENTATION OF A MULTI -ROBOT COVERAGE ALGORITHM ON A TWO -DIMENSIONAL, GRID-BASED ENVIRONMENT 5. FUNDING NUMBERS...path planning coverage algorithm for a multi -robot system in a two -dimensional, grid-based environment. We assess the applicability of a topology
NASA Technical Reports Server (NTRS)
Liu, Kuojuey Ray
1990-01-01
Least-squares (LS) estimations and spectral decomposition algorithms constitute the heart of modern signal processing and communication problems. Implementations of recursive LS and spectral decomposition algorithms onto parallel processing architectures such as systolic arrays with efficient fault-tolerant schemes are the major concerns of this dissertation. There are four major results in this dissertation. First, we propose the systolic block Householder transformation with application to the recursive least-squares minimization. It is successfully implemented on a systolic array with a two-level pipelined implementation at the vector level as well as at the word level. Second, a real-time algorithm-based concurrent error detection scheme based on the residual method is proposed for the QRD RLS systolic array. The fault diagnosis, order degraded reconfiguration, and performance analysis are also considered. Third, the dynamic range, stability, error detection capability under finite-precision implementation, order degraded performance, and residual estimation under faulty situations for the QRD RLS systolic array are studied in details. Finally, we propose the use of multi-phase systolic algorithms for spectral decomposition based on the QR algorithm. Two systolic architectures, one based on triangular array and another based on rectangular array, are presented for the multiphase operations with fault-tolerant considerations. Eigenvectors and singular vectors can be easily obtained by using the multi-pase operations. Performance issues are also considered.
Nanotechnology: The Incredible Invisible World
ERIC Educational Resources Information Center
Roberts, Amanda S.
2011-01-01
The concept of nanotechnology was first introduced in 1959 by Richard Feynman at a meeting of the American Physical Society. Nanotechnology opens the door to an exciting new science/technology/engineering field. The possibilities for the uses of this technology should inspire the imagination to think big. Many are already pursuing such feats…
Laboratory for Computer Science Progress Report 18, July 1980-June 1981,
1983-04-01
group in collaboration with Rolf Landauer of IBM Research. Some of the most conspicuous participants: Dyson, Feynman, Wheeler Landauer, Keyes, Bennett...Sheldon A. Data Model Equivalence, December 1978, AD A062-753 TM-119 Shamir, Adi and Richard E. Zippel On the Security of the Merkle -Hellman
Perturbative test of exact vacuum expectation values of local fields in affine Toda theories
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ahn, Changrim; Baseilhac, P.; Kim, Chanju
Vacuum expectation values of local fields for all dual pairs of nonsimply laced affine Toda field theories recently proposed are checked against perturbative analysis. The computations based on Feynman diagram expansion are performed up to the two-loop level. We obtain, good agreement.
Optimization and experimental realization of the quantum permutation algorithm
NASA Astrophysics Data System (ADS)
Yalçınkaya, I.; Gedik, Z.
2017-12-01
The quantum permutation algorithm provides computational speed-up over classical algorithms for determining the parity of a given cyclic permutation. For its n -qubit implementations, the number of required quantum gates scales quadratically with n due to the quantum Fourier transforms included. We show here for the n -qubit case that the algorithm can be simplified so that it requires only O (n ) quantum gates, which theoretically reduces the complexity of the implementation. To test our results experimentally, we utilize IBM's 5-qubit quantum processor to realize the algorithm by using the original and simplified recipes for the 2-qubit case. It turns out that the latter results in a significantly higher success probability which allows us to verify the algorithm more precisely than the previous experimental realizations. We also verify the algorithm for the first time for the 3-qubit case with a considerable success probability by taking the advantage of our simplified scheme.
NASA Technical Reports Server (NTRS)
Schoenwald, Adam J.; Bradley, Damon C.; Mohammed, Priscilla N.; Piepmeier, Jeffrey R.; Wong, Mark
2016-01-01
Radio-frequency interference (RFI) is a known problem for passive remote sensing as evidenced in the L-band radiometers SMOS, Aquarius and more recently, SMAP. Various algorithms have been developed and implemented on SMAP to improve science measurements. This was achieved by the use of a digital microwave radiometer. RFI mitigation becomes more challenging for microwave radiometers operating at higher frequencies in shared allocations. At higher frequencies larger bandwidths are also desirable for lower measurement noise further adding to processing challenges. This work focuses on finding improved RFI mitigation techniques that will be effective at additional frequencies and at higher bandwidths. To aid the development and testing of applicable detection and mitigation techniques, a wide-band RFI algorithm testing environment has been developed using the Reconfigurable Open Architecture Computing Hardware System (ROACH) built by the Collaboration for Astronomy Signal Processing and Electronics Research (CASPER) Group. The testing environment also consists of various test equipment used to reproduce typical signals that a radiometer may see including those with and without RFI. The testing environment permits quick evaluations of RFI mitigation algorithms as well as show that they are implementable in hardware. The algorithm implemented is a complex signal kurtosis detector which was modeled and simulated. The complex signal kurtosis detector showed improved performance over the real kurtosis detector under certain conditions. The real kurtosis is implemented on SMAP at 24 MHz bandwidth. The complex signal kurtosis algorithm was then implemented in hardware at 200 MHz bandwidth using the ROACH. In this work, performance of the complex signal kurtosis and the real signal kurtosis are compared. Performance evaluations and comparisons in both simulation as well as experimental hardware implementations were done with the use of receiver operating characteristic (ROC) curves.
Symbolic Solution of Linear Differential Equations
NASA Technical Reports Server (NTRS)
Feinberg, R. B.; Grooms, R. G.
1981-01-01
An algorithm for solving linear constant-coefficient ordinary differential equations is presented. The computational complexity of the algorithm is discussed and its implementation in the FORMAC system is described. A comparison is made between the algorithm and some classical algorithms for solving differential equations.
Design Report for Low Power Acoustic Detector
2013-08-01
high speed integrated circuit (VHSIC) hardware description language ( VHDL ) implementation of both the HED and DCD detectors. Figures 4 and 5 show the...the hardware design, target detection algorithm design in both MATLAB and VHDL , and typical performance results. 15. SUBJECT TERMS Acoustic low...5 2.4 Algorithm Implementation ..............................................................................................6 3. Testing
Algorithm Visualization System for Teaching Spatial Data Algorithms
ERIC Educational Resources Information Center
Nikander, Jussi; Helminen, Juha; Korhonen, Ari
2010-01-01
TRAKLA2 is a web-based learning environment for data structures and algorithms. The system delivers automatically assessed algorithm simulation exercises that are solved using a graphical user interface. In this work, we introduce a novel learning environment for spatial data algorithms, SDA-TRAKLA2, which has been implemented on top of the…
Public-key encryption with chaos.
Kocarev, Ljupco; Sterjev, Marjan; Fekete, Attila; Vattay, Gabor
2004-12-01
We propose public-key encryption algorithms based on chaotic maps, which are generalization of well-known and commercially used algorithms: Rivest-Shamir-Adleman (RSA), ElGamal, and Rabin. For the case of generalized RSA algorithm we discuss in detail its software implementation and properties. We show that our algorithm is as secure as RSA algorithm.
Public-key encryption with chaos
NASA Astrophysics Data System (ADS)
Kocarev, Ljupco; Sterjev, Marjan; Fekete, Attila; Vattay, Gabor
2004-12-01
We propose public-key encryption algorithms based on chaotic maps, which are generalization of well-known and commercially used algorithms: Rivest-Shamir-Adleman (RSA), ElGamal, and Rabin. For the case of generalized RSA algorithm we discuss in detail its software implementation and properties. We show that our algorithm is as secure as RSA algorithm.
NASA Astrophysics Data System (ADS)
Hadia, Sarman K.; Thakker, R. A.; Bhatt, Kirit R.
2016-05-01
The study proposes an application of evolutionary algorithms, specifically an artificial bee colony (ABC), variant ABC and particle swarm optimisation (PSO), to extract the parameters of metal oxide semiconductor field effect transistor (MOSFET) model. These algorithms are applied for the MOSFET parameter extraction problem using a Pennsylvania surface potential model. MOSFET parameter extraction procedures involve reducing the error between measured and modelled data. This study shows that ABC algorithm optimises the parameter values based on intelligent activities of honey bee swarms. Some modifications have also been applied to the basic ABC algorithm. Particle swarm optimisation is a population-based stochastic optimisation method that is based on bird flocking activities. The performances of these algorithms are compared with respect to the quality of the solutions. The simulation results of this study show that the PSO algorithm performs better than the variant ABC and basic ABC algorithm for the parameter extraction of the MOSFET model; also the implementation of the ABC algorithm is shown to be simpler than that of the PSO algorithm.
A fast method to emulate an iterative POCS image reconstruction algorithm.
Zeng, Gengsheng L
2017-10-01
Iterative image reconstruction algorithms are commonly used to optimize an objective function, especially when the objective function is nonquadratic. Generally speaking, the iterative algorithms are computationally inefficient. This paper presents a fast algorithm that has one backprojection and no forward projection. This paper derives a new method to solve an optimization problem. The nonquadratic constraint, for example, an edge-preserving denoising constraint is implemented as a nonlinear filter. The algorithm is derived based on the POCS (projections onto projections onto convex sets) approach. A windowed FBP (filtered backprojection) algorithm enforces the data fidelity. An iterative procedure, divided into segments, enforces edge-enhancement denoising. Each segment performs nonlinear filtering. The derived iterative algorithm is computationally efficient. It contains only one backprojection and no forward projection. Low-dose CT data are used for algorithm feasibility studies. The nonlinearity is implemented as an edge-enhancing noise-smoothing filter. The patient studies results demonstrate its effectiveness in processing low-dose x ray CT data. This fast algorithm can be used to replace many iterative algorithms. © 2017 American Association of Physicists in Medicine.
Improved pulse laser ranging algorithm based on high speed sampling
NASA Astrophysics Data System (ADS)
Gao, Xuan-yi; Qian, Rui-hai; Zhang, Yan-mei; Li, Huan; Guo, Hai-chao; He, Shi-jie; Guo, Xiao-kang
2016-10-01
Narrow pulse laser ranging achieves long-range target detection using laser pulse with low divergent beams. Pulse laser ranging is widely used in military, industrial, civil, engineering and transportation field. In this paper, an improved narrow pulse laser ranging algorithm is studied based on the high speed sampling. Firstly, theoretical simulation models have been built and analyzed including the laser emission and pulse laser ranging algorithm. An improved pulse ranging algorithm is developed. This new algorithm combines the matched filter algorithm and the constant fraction discrimination (CFD) algorithm. After the algorithm simulation, a laser ranging hardware system is set up to implement the improved algorithm. The laser ranging hardware system includes a laser diode, a laser detector and a high sample rate data logging circuit. Subsequently, using Verilog HDL language, the improved algorithm is implemented in the FPGA chip based on fusion of the matched filter algorithm and the CFD algorithm. Finally, the laser ranging experiment is carried out to test the improved algorithm ranging performance comparing to the matched filter algorithm and the CFD algorithm using the laser ranging hardware system. The test analysis result demonstrates that the laser ranging hardware system realized the high speed processing and high speed sampling data transmission. The algorithm analysis result presents that the improved algorithm achieves 0.3m distance ranging precision. The improved algorithm analysis result meets the expected effect, which is consistent with the theoretical simulation.
Massanes, Francesc; Cadennes, Marie; Brankov, Jovan G.
2012-01-01
In this paper we describe and evaluate a fast implementation of a classical block matching motion estimation algorithm for multiple Graphical Processing Units (GPUs) using the Compute Unified Device Architecture (CUDA) computing engine. The implemented block matching algorithm (BMA) uses summed absolute difference (SAD) error criterion and full grid search (FS) for finding optimal block displacement. In this evaluation we compared the execution time of a GPU and CPU implementation for images of various sizes, using integer and non-integer search grids. The results show that use of a GPU card can shorten computation time by a factor of 200 times for integer and 1000 times for a non-integer search grid. The additional speedup for non-integer search grid comes from the fact that GPU has built-in hardware for image interpolation. Further, when using multiple GPU cards, the presented evaluation shows the importance of the data splitting method across multiple cards, but an almost linear speedup with a number of cards is achievable. In addition we compared execution time of the proposed FS GPU implementation with two existing, highly optimized non-full grid search CPU based motion estimations methods, namely implementation of the Pyramidal Lucas Kanade Optical flow algorithm in OpenCV and Simplified Unsymmetrical multi-Hexagon search in H.264/AVC standard. In these comparisons, FS GPU implementation still showed modest improvement even though the computational complexity of FS GPU implementation is substantially higher than non-FS CPU implementation. We also demonstrated that for an image sequence of 720×480 pixels in resolution, commonly used in video surveillance, the proposed GPU implementation is sufficiently fast for real-time motion estimation at 30 frames-per-second using two NVIDIA C1060 Tesla GPU cards. PMID:22347787
Massanes, Francesc; Cadennes, Marie; Brankov, Jovan G
2011-07-01
In this paper we describe and evaluate a fast implementation of a classical block matching motion estimation algorithm for multiple Graphical Processing Units (GPUs) using the Compute Unified Device Architecture (CUDA) computing engine. The implemented block matching algorithm (BMA) uses summed absolute difference (SAD) error criterion and full grid search (FS) for finding optimal block displacement. In this evaluation we compared the execution time of a GPU and CPU implementation for images of various sizes, using integer and non-integer search grids.The results show that use of a GPU card can shorten computation time by a factor of 200 times for integer and 1000 times for a non-integer search grid. The additional speedup for non-integer search grid comes from the fact that GPU has built-in hardware for image interpolation. Further, when using multiple GPU cards, the presented evaluation shows the importance of the data splitting method across multiple cards, but an almost linear speedup with a number of cards is achievable.In addition we compared execution time of the proposed FS GPU implementation with two existing, highly optimized non-full grid search CPU based motion estimations methods, namely implementation of the Pyramidal Lucas Kanade Optical flow algorithm in OpenCV and Simplified Unsymmetrical multi-Hexagon search in H.264/AVC standard. In these comparisons, FS GPU implementation still showed modest improvement even though the computational complexity of FS GPU implementation is substantially higher than non-FS CPU implementation.We also demonstrated that for an image sequence of 720×480 pixels in resolution, commonly used in video surveillance, the proposed GPU implementation is sufficiently fast for real-time motion estimation at 30 frames-per-second using two NVIDIA C1060 Tesla GPU cards.
Congdon, Heather Brennan; Eldridge, Barbara Hoffman; Truong, Hoai-An
2013-11-01
Development and implementation of an interprofessional navigator-facilitated care coordination algorithm (NAVCOM) for low-income, uninsured patients with uncontrolled diabetes at a safety-net clinic resulted in improvement of disease control as evidenced by improvement in hemoglobin A1C. This report describes the process and lessons learned from the development and implementation of NAVCOM and patient success stories.
Sorensen, Lene; Nielsen, Bent; Stage, Kurt B; Brøsen, Kim; Damkier, Per
2008-01-01
The objective of the study was to develop, implement and evaluate two treatment algorithms for schizophrenia and depression at a psychiatric hospital department. The treatment algorithms were based on available literature and developed in collaboration between psychiatrists, clinical pharmacologists and a clinical pharmacist. The treatment algorithms were introduced at a meeting for all psychiatrists, reinforced by the project psychiatrists in the daily routine and used for educational purposes of young doctors and medical students. A quantitative pre-post evaluation was conducted using data from medical charts, and qualitative information was collected by interviews. In general, no significant differences were found when comparing outcomes from 104 charts from the baseline period with 96 charts from the post-intervention period. Most of the patients (65% in the post-intervention period) admitted during the data collection periods did not receive any medication changes. Of the patients undergoing medication changes in the post-intervention period, 56% followed the algorithms, and 70% of the patients admitted to the psychiatric hospital department for the first time had their medications changed according to the algorithms. All of the 10 interviewed doctors found the algorithms useful. The treatment algorithms were successfully implemented with a high degree of satisfaction among the interviewed doctors. The majority of patients admitted to the psychiatric hospital department for the first time had their medications changed according to the algorithms.
A pipelined FPGA implementation of an encryption algorithm based on genetic algorithm
NASA Astrophysics Data System (ADS)
Thirer, Nonel
2013-05-01
With the evolution of digital data storage and exchange, it is essential to protect the confidential information from every unauthorized access. High performance encryption algorithms were developed and implemented by software and hardware. Also many methods to attack the cipher text were developed. In the last years, the genetic algorithm has gained much interest in cryptanalysis of cipher texts and also in encryption ciphers. This paper analyses the possibility to use the genetic algorithm as a multiple key sequence generator for an AES (Advanced Encryption Standard) cryptographic system, and also to use a three stages pipeline (with four main blocks: Input data, AES Core, Key generator, Output data) to provide a fast encryption and storage/transmission of a large amount of data.
Peng, Bo; Wang, Yuqi; Hall, Timothy J; Jiang, Jingfeng
2017-01-01
Our primary objective of this work was to extend a previously published 2D coupled sub-sample tracking algorithm for 3D speckle tracking in the framework of ultrasound breast strain elastography. In order to overcome heavy computational cost, we investigated the use of a graphic processing unit (GPU) to accelerate the 3D coupled sub-sample speckle tracking method. The performance of the proposed GPU implementation was tested using a tissue-mimicking (TM) phantom and in vivo breast ultrasound data. The performance of this 3D sub-sample tracking algorithm was compared with the conventional 3D quadratic sub-sample estimation algorithm. On the basis of these evaluations, we concluded that the GPU implementation of this 3D sub-sample estimation algorithm can provide high-quality strain data (i.e. high correlation between the pre- and the motion-compensated post-deformation RF echo data and high contrast-to-noise ratio strain images), as compared to the conventional 3D quadratic sub-sample algorithm. Using the GPU implementation of the 3D speckle tracking algorithm, volumetric strain data can be achieved relatively fast (approximately 20 seconds per volume [2.5 cm × 2.5 cm × 2.5 cm]). PMID:28166493
Effective algorithm for routing integral structures with twolayer switching
NASA Astrophysics Data System (ADS)
Nazarov, A. V.; Shakhnov, V. A.; Vlasov, A. I.; Novikov, A. N.
2018-05-01
The paper presents an algorithm for routing switching objects such as large-scale integrated circuits (LSICs) with two layers of metallization, embossed printed circuit boards, microboards with pairs of wiring layers on each side, and other similar constructs. The algorithm allows eliminating the effect of mutual blocking of routes in the classical wave algorithm by implementing a special circuit of digital wave motion in two layers of metallization, allowing direct intersections of all circuit conductors in a combined layer. However, information about the belonging of the topology elements to the circuits is sufficient for layering and minimizing the number of contact holes. In addition, the paper presents a specific example which shows that, in contrast to the known routing algorithms using a wave model, just one byte of memory per discrete of the work field is sufficient to implement the proposed algorithm.
The MINERVA Software Development Process
NASA Technical Reports Server (NTRS)
Narkawicz, Anthony; Munoz, Cesar A.; Dutle, Aaron M.
2017-01-01
This paper presents a software development process for safety-critical software components of cyber-physical systems. The process is called MINERVA, which stands for Mirrored Implementation Numerically Evaluated against Rigorously Verified Algorithms. The process relies on formal methods for rigorously validating code against its requirements. The software development process uses: (1) a formal specification language for describing the algorithms and their functional requirements, (2) an interactive theorem prover for formally verifying the correctness of the algorithms, (3) test cases that stress the code, and (4) numerical evaluation on these test cases of both the algorithm specifications and their implementations in code. The MINERVA process is illustrated in this paper with an application to geo-containment algorithms for unmanned aircraft systems. These algorithms ensure that the position of an aircraft never leaves a predetermined polygon region and provide recovery maneuvers when the region is inadvertently exited.
On the VLSI design of a pipeline Reed-Solomon decoder using systolic arrays
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shao, H.M.; Reed, I.S.
A new VLSI design of a pipeline Reed-Solomon decoder is presented. The transform decoding technique used in a previous paper is replaced by a time domain algorithm through a detailed comparison of their VLSI implementations. A new architecture that implements the time domain algorithm permits efficient pipeline processing with reduced circuitry. Erasure correction capability is also incorporated with little additional complexity. By using a multiplexing technique, a new implementation of Euclid's algorithm maintains the throughput rate with less circuitry. Such improvements result in both enhanced capability and significant reduction in silicon area, therefore making it possible to build a pipelinemore » Reed-Solomon decoder on a single VLSI chip.« less
A high performance hardware implementation image encryption with AES algorithm
NASA Astrophysics Data System (ADS)
Farmani, Ali; Jafari, Mohamad; Miremadi, Seyed Sohrab
2011-06-01
This paper describes implementation of a high-speed encryption algorithm with high throughput for encrypting the image. Therefore, we select a highly secured symmetric key encryption algorithm AES(Advanced Encryption Standard), in order to increase the speed and throughput using pipeline technique in four stages, control unit based on logic gates, optimal design of multiplier blocks in mixcolumn phase and simultaneous production keys and rounds. Such procedure makes AES suitable for fast image encryption. Implementation of a 128-bit AES on FPGA of Altra company has been done and the results are as follow: throughput, 6 Gbps in 471MHz. The time of encrypting in tested image with 32*32 size is 1.15ms.
Distributed Prognostic Health Management with Gaussian Process Regression
NASA Technical Reports Server (NTRS)
Saha, Sankalita; Saha, Bhaskar; Saxena, Abhinav; Goebel, Kai Frank
2010-01-01
Distributed prognostics architecture design is an enabling step for efficient implementation of health management systems. A major challenge encountered in such design is formulation of optimal distributed prognostics algorithms. In this paper. we present a distributed GPR based prognostics algorithm whose target platform is a wireless sensor network. In addition to challenges encountered in a distributed implementation, a wireless network poses constraints on communication patterns, thereby making the problem more challenging. The prognostics application that was used to demonstrate our new algorithms is battery prognostics. In order to present trade-offs within different prognostic approaches, we present comparison with the distributed implementation of a particle filter based prognostics for the same battery data.
Modular Toolkit for Data Processing (MDP): A Python Data Processing Framework.
Zito, Tiziano; Wilbert, Niko; Wiskott, Laurenz; Berkes, Pietro
2008-01-01
Modular toolkit for Data Processing (MDP) is a data processing framework written in Python. From the user's perspective, MDP is a collection of supervised and unsupervised learning algorithms and other data processing units that can be combined into data processing sequences and more complex feed-forward network architectures. Computations are performed efficiently in terms of speed and memory requirements. From the scientific developer's perspective, MDP is a modular framework, which can easily be expanded. The implementation of new algorithms is easy and intuitive. The new implemented units are then automatically integrated with the rest of the library. MDP has been written in the context of theoretical research in neuroscience, but it has been designed to be helpful in any context where trainable data processing algorithms are used. Its simplicity on the user's side, the variety of readily available algorithms, and the reusability of the implemented units make it also a useful educational tool.
ELF: An Extended-Lagrangian Free Energy Calculation Module for Multiple Molecular Dynamics Engines.
Chen, Haochuan; Fu, Haohao; Shao, Xueguang; Chipot, Christophe; Cai, Wensheng
2018-06-18
Extended adaptive biasing force (eABF), a collective variable (CV)-based importance-sampling algorithm, has proven to be very robust and efficient compared with the original ABF algorithm. Its implementation in Colvars, a software addition to molecular dynamics (MD) engines, is, however, currently limited to NAMD and LAMMPS. To broaden the scope of eABF and its variants, like its generalized form (egABF), and make them available to other MD engines, e.g., GROMACS, AMBER, CP2K, and openMM, we present a PLUMED-based implementation, called extended-Lagrangian free energy calculation (ELF). This implementation can be used as a stand-alone gradient estimator for other CV-based sampling algorithms, such as temperature-accelerated MD (TAMD) and extended-Lagrangian metadynamics (MtD). ELF provides the end user with a convenient framework to help select the best-suited importance-sampling algorithm for a given application without any commitment to a particular MD engine.
Implementation of Maximum Power Point Tracking (MPPT) Solar Charge Controller using Arduino
NASA Astrophysics Data System (ADS)
Abdelilah, B.; Mouna, A.; KouiderM’Sirdi, N.; El Hossain, A.
2018-05-01
the platform Arduino with a number of sensors standard can be used as components of an electronic system for acquiring measures and controls. This paper presents the design of a low-cost and effective solar charge controller. This system includes several elements such as the solar panel converter DC/DC, battery, circuit MPPT using Microcontroller, sensors, and the MPPT algorithm. The MPPT (Maximum Power Point Tracker) algorithm has been implemented using an Arduino Nano with the preferred program. The voltage and current of the Panel are taken where the program implemented will work and using this algorithm that MPP will be reached. This paper provides details on the solar charge control device at the maximum power point. The results include the change of the duty cycle with the change in load and thus mean the variation of the buck converter output voltage and current controlled by the MPPT algorithm.
Variational optimization algorithms for uniform matrix product states
NASA Astrophysics Data System (ADS)
Zauner-Stauber, V.; Vanderstraeten, L.; Fishman, M. T.; Verstraete, F.; Haegeman, J.
2018-01-01
We combine the density matrix renormalization group (DMRG) with matrix product state tangent space concepts to construct a variational algorithm for finding ground states of one-dimensional quantum lattices in the thermodynamic limit. A careful comparison of this variational uniform matrix product state algorithm (VUMPS) with infinite density matrix renormalization group (IDMRG) and with infinite time evolving block decimation (ITEBD) reveals substantial gains in convergence speed and precision. We also demonstrate that VUMPS works very efficiently for Hamiltonians with long-range interactions and also for the simulation of two-dimensional models on infinite cylinders. The new algorithm can be conveniently implemented as an extension of an already existing DMRG implementation.
The upwind control volume scheme for unstructured triangular grids
NASA Technical Reports Server (NTRS)
Giles, Michael; Anderson, W. Kyle; Roberts, Thomas W.
1989-01-01
A new algorithm for the numerical solution of the Euler equations is presented. This algorithm is particularly suited to the use of unstructured triangular meshes, allowing geometric flexibility. Solutions are second-order accurate in the steady state. Implementation of the algorithm requires minimal grid connectivity information, resulting in modest storage requirements, and should enhance the implementation of the scheme on massively parallel computers. A novel form of upwind differencing is developed, and is shown to yield sharp resolution of shocks. Two new artificial viscosity models are introduced that enhance the performance of the new scheme. Numerical results for transonic airfoil flows are presented, which demonstrate the performance of the algorithm.
Graphene-based room-temperature implementation of a modified Deutsch-Jozsa quantum algorithm.
Dragoman, Daniela; Dragoman, Mircea
2015-12-04
We present an implementation of a one-qubit and two-qubit modified Deutsch-Jozsa quantum algorithm based on graphene ballistic devices working at room temperature. The modified Deutsch-Jozsa algorithm decides whether a function, equivalent to the effect of an energy potential distribution on the wave function of ballistic charge carriers, is constant or not, without measuring the output wave function. The function need not be Boolean. Simulations confirm that the algorithm works properly, opening the way toward quantum computing at room temperature based on the same clean-room technologies as those used for fabrication of very-large-scale integrated circuits.
Efficient parallel implementation of active appearance model fitting algorithm on GPU.
Wang, Jinwei; Ma, Xirong; Zhu, Yuanping; Sun, Jizhou
2014-01-01
The active appearance model (AAM) is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to real-time systems. The emergence of modern graphics processing units (GPUs) that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. In this paper, we propose an efficient parallel implementation of the AAM fitting algorithm on GPUs. Our design idea is fine grain parallelism in which we distribute the texture data of the AAM, in pixels, to thousands of parallel GPU threads for processing, which makes the algorithm fit better into the GPU architecture. We implement our algorithm using the compute unified device architecture (CUDA) on the Nvidia's GTX 650 GPU, which has the latest Kepler architecture. To compare the performance of our algorithm with different data sizes, we built sixteen face AAM models of different dimensional textures. The experiment results show that our parallel AAM fitting algorithm can achieve real-time performance for videos even on very high-dimensional textures.
Efficient Parallel Implementation of Active Appearance Model Fitting Algorithm on GPU
Wang, Jinwei; Ma, Xirong; Zhu, Yuanping; Sun, Jizhou
2014-01-01
The active appearance model (AAM) is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to real-time systems. The emergence of modern graphics processing units (GPUs) that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. In this paper, we propose an efficient parallel implementation of the AAM fitting algorithm on GPUs. Our design idea is fine grain parallelism in which we distribute the texture data of the AAM, in pixels, to thousands of parallel GPU threads for processing, which makes the algorithm fit better into the GPU architecture. We implement our algorithm using the compute unified device architecture (CUDA) on the Nvidia's GTX 650 GPU, which has the latest Kepler architecture. To compare the performance of our algorithm with different data sizes, we built sixteen face AAM models of different dimensional textures. The experiment results show that our parallel AAM fitting algorithm can achieve real-time performance for videos even on very high-dimensional textures. PMID:24723812
DOE Office of Scientific and Technical Information (OSTI.GOV)
Karlsson, Niklas
Observations of gamma-rays have been made from celestial sources such as active galaxies, gamma-ray bursts and supernova remnants as well as the Galactic ridge. The study of gamma rays can provide information about production mechanisms and cosmic-ray acceleration. In the high-energy regime, one of the dominant mechanisms for gamma-ray production is the decay of neutral pions produced in interactions of ultra-relativistic cosmic-ray nuclei and interstellar matter. Presented here is a parametric model for calculations of inclusive cross sections and transverse momentum distributions for secondary particles--gamma rays, e ±, v e,more » $$\\bar{v}$$ e, v μ and $$\\bar{μ}$$ e--produced in proton-proton interactions. This parametric model is derived on the proton-proton interaction model proposed by Kamae et al.; it includes the diffraction dissociation process, Feynman-scaling violation and the logarithmically rising inelastic proton-proton cross section. To improve fidelity to experimental data for lower energies, two baryon resonance excitation processes were added; one representing the Δ(1232) and the other multiple resonances with masses around 1600 MeV/c 2. The model predicts the power-law spectral index for all secondary particle to be about 0.05 lower in absolute value than that of the incident proton and their inclusive cross sections to be larger than those predicted by previous models based on the Feynman-scaling hypothesis. The applications of the presented model in astrophysics are plentiful. It has been implemented into the Galprop code to calculate the contribution due to pion decays in the Galactic plane. The model has also been used to estimate the cosmic-ray flux in the Large Magellanic Cloud based on HI, CO and gamma-ray observations. The transverse momentum distributions enable calculations when the proton distribution is anisotropic. It is shown that the gamma-ray spectrum and flux due to a pencil beam of protons varies drastically with viewing angle. A fanned proton jet with a Gaussian intensity profile impinging on surrounding material is given as a more realistic example. As the observer is moved off the jet axis, the peak of the spectrum is moved to lower energies.« less
FeynArts model file for MSSM transition counterterms from DREG to DRED
NASA Astrophysics Data System (ADS)
Stöckinger, Dominik; Varšo, Philipp
2012-02-01
The FeynArts model file MSSMdreg2dred implements MSSM transition counterterms which can convert one-loop Green functions from dimensional regularization to dimensional reduction. They correspond to a slight extension of the well-known Martin/Vaughn counterterms, specialized to the MSSM, and can serve also as supersymmetry-restoring counterterms. The paper provides full analytic results for the counterterms and gives one- and two-loop usage examples. The model file can simplify combining MS¯-parton distribution functions with supersymmetric renormalization or avoiding the renormalization of ɛ-scalars in dimensional reduction. Program summaryProgram title:MSSMdreg2dred.mod Catalogue identifier: AEKR_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEKR_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: LGPL-License [1] No. of lines in distributed program, including test data, etc.: 7600 No. of bytes in distributed program, including test data, etc.: 197 629 Distribution format: tar.gz Programming language: Mathematica, FeynArts Computer: Any, capable of running Mathematica and FeynArts Operating system: Any, with running Mathematica, FeynArts installation Classification: 4.4, 5, 11.1 Subprograms used: Cat Id Title Reference ADOW_v1_0 FeynArts CPC 140 (2001) 418 Nature of problem: The computation of one-loop Feynman diagrams in the minimal supersymmetric standard model (MSSM) requires regularization. Two schemes, dimensional regularization and dimensional reduction are both common but have different pros and cons. In order to combine the advantages of both schemes one would like to easily convert existing results from one scheme into the other. Solution method: Finite counterterms are constructed which correspond precisely to the one-loop scheme differences for the MSSM. They are provided as a FeynArts [2] model file. Using this model file together with FeynArts, the (ultra-violet) regularization of any MSSM one-loop Green function is switched automatically from dimensional regularization to dimensional reduction. In particular the counterterms serve as supersymmetry-restoring counterterms for dimensional regularization. Restrictions: The counterterms are restricted to the one-loop level and the MSSM. Running time: A few seconds to generate typical Feynman graphs with FeynArts.
VLSI chip-set for data compression using the Rice algorithm
NASA Technical Reports Server (NTRS)
Venbrux, J.; Liu, N.
1990-01-01
A full custom VLSI implementation of a data compression encoder and decoder which implements the lossless Rice data compression algorithm is discussed in this paper. The encoder and decoder reside on single chips. The data rates are to be 5 and 10 Mega-samples-per-second for the decoder and encoder respectively.
ERIC Educational Resources Information Center
Auberry, Kathy; Cullen, Deborah
2016-01-01
Based on the results of the Surrogate Decision-Making Self Efficacy Scale (Lopez, 2009a), this study sought to determine whether nurses working in the field of intellectual disability (ID) experience increased confidence when they implemented the American Association of Neuroscience Nurses (AANN) Seizure Algorithm during telephone triage. The…
Computational Discovery of Materials Using the Firefly Algorithm
NASA Astrophysics Data System (ADS)
Avendaño-Franco, Guillermo; Romero, Aldo
Our current ability to model physical phenomena accurately, the increase computational power and better algorithms are the driving forces behind the computational discovery and design of novel materials, allowing for virtual characterization before their realization in the laboratory. We present the implementation of a novel firefly algorithm, a population-based algorithm for global optimization for searching the structure/composition space. This novel computation-intensive approach naturally take advantage of concurrency, targeted exploration and still keeping enough diversity. We apply the new method in both periodic and non-periodic structures and we present the implementation challenges and solutions to improve efficiency. The implementation makes use of computational materials databases and network analysis to optimize the search and get insights about the geometric structure of local minima on the energy landscape. The method has been implemented in our software PyChemia, an open-source package for materials discovery. We acknowledge the support of DMREF-NSF 1434897 and the Donors of the American Chemical Society Petroleum Research Fund for partial support of this research under Contract 54075-ND10.
Farris, Dominic James; Lichtwark, Glen A
2016-05-01
Dynamic measurements of human muscle fascicle length from sequences of B-mode ultrasound images have become increasingly prevalent in biomedical research. Manual digitisation of these images is time consuming and algorithms for automating the process have been developed. Here we present a freely available software implementation of a previously validated algorithm for semi-automated tracking of muscle fascicle length in dynamic ultrasound image recordings, "UltraTrack". UltraTrack implements an affine extension to an optic flow algorithm to track movement of the muscle fascicle end-points throughout dynamically recorded sequences of images. The underlying algorithm has been previously described and its reliability tested, but here we present the software implementation with features for: tracking multiple fascicles in multiple muscles simultaneously; correcting temporal drift in measurements; manually adjusting tracking results; saving and re-loading of tracking results and loading a range of file formats. Two example runs of the software are presented detailing the tracking of fascicles from several lower limb muscles during a squatting and walking activity. We have presented a software implementation of a validated fascicle-tracking algorithm and made the source code and standalone versions freely available for download. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Botti, Mari; Kent, Bridie; Bucknall, Tracey; Duke, Maxine; Johnstone, Megan-Jane; Considine, Julie; Redley, Bernice; Hunter, Susan; de Steiger, Richard; Holcombe, Marlene; Cohen, Emma
2014-08-28
Evidence from clinical practice and the extant literature suggests that post-operative pain assessment and treatment is often suboptimal. Poor pain management is likely to persist until pain management practices become consistent with guidelines developed from the best available scientific evidence. This work will address the priority in healthcare of improving the quality of pain management by standardising evidence-based care processes through the incorporation of an algorithm derived from best evidence into clinical practice. In this paper, the methodology for the creation and implementation of such an algorithm that will focus, in the first instance, on patients who have undergone total hip or knee replacement is described. In partnership with clinicians, and based on best available evidence, the aim of the Management Algorithm for Post-operative Pain (MAPP) project is to develop, implement, and evaluate an algorithm designed to support pain management decision-making for patients after orthopaedic surgery. The algorithm will provide guidance for the prescription and administration of multimodal analgesics in the post-operative period, and the treatment of breakthrough pain. The MAPP project is a multisite study with one coordinating hospital and two supporting (rollout) hospitals. The design of this project is a pre-implementation-post-implementation evaluation and will be conducted over three phases. The Promoting Action on Research Implementation in Health Services (PARiHS) framework will be used to guide implementation. Outcome measurements will be taken 10 weeks post-implementation of the MAPP. The primary outcomes are: proportion of patients prescribed multimodal analgesics in accordance with the MAPP; and proportion of patients with moderate to severe pain intensity at rest. These data will be compared to the pre-implementation analgesic prescribing practices and pain outcome measures. A secondary outcome, the efficacy of the MAPP, will be measured by comparing pain intensity scores of patients where the MAPP guidelines were or were not followed. The outcomes of this study have relevance for nursing and medical professionals as well as informing health service evaluation. In establishing a framework for the sustainable implementation and evaluation of a standardised approach to post-operative pain management, the findings have implications for clinicians and patients within multiple surgical contexts.
Hardware Implementation of Lossless Adaptive Compression of Data From a Hyperspectral Imager
NASA Technical Reports Server (NTRS)
Keymeulen, Didlier; Aranki, Nazeeh I.; Klimesh, Matthew A.; Bakhshi, Alireza
2012-01-01
Efficient onboard data compression can reduce the data volume from hyperspectral imagers on NASA and DoD spacecraft in order to return as much imagery as possible through constrained downlink channels. Lossless compression is important for signature extraction, object recognition, and feature classification capabilities. To provide onboard data compression, a hardware implementation of a lossless hyperspectral compression algorithm was developed using a field programmable gate array (FPGA). The underlying algorithm is the Fast Lossless (FL) compression algorithm reported in Fast Lossless Compression of Multispectral- Image Data (NPO-42517), NASA Tech Briefs, Vol. 30, No. 8 (August 2006), p. 26 with the modification reported in Lossless, Multi-Spectral Data Comressor for Improved Compression for Pushbroom-Type Instruments (NPO-45473), NASA Tech Briefs, Vol. 32, No. 7 (July 2008) p. 63, which provides improved compression performance for data from pushbroom-type imagers. An FPGA implementation of the unmodified FL algorithm was previously developed and reported in Fast and Adaptive Lossless Onboard Hyperspectral Data Compression System (NPO-46867), NASA Tech Briefs, Vol. 36, No. 5 (May 2012) p. 42. The essence of the FL algorithm is adaptive linear predictive compression using the sign algorithm for filter adaption. The FL compressor achieves a combination of low complexity and compression effectiveness that exceeds that of stateof- the-art techniques currently in use. The modification changes the predictor structure to tolerate differences in sensitivity of different detector elements, as occurs in pushbroom-type imagers, which are suitable for spacecraft use. The FPGA implementation offers a low-cost, flexible solution compared to traditional ASIC (application specific integrated circuit) and can be integrated as an intellectual property (IP) for part of, e.g., a design that manages the instrument interface. The FPGA implementation was benchmarked on the Xilinx Virtex IV LX25 device, and ported to a Xilinx prototype board. The current implementation has a critical path of 29.5 ns, which dictated a clock speed of 33 MHz. The critical path delay is end-to-end measurement between the uncompressed input data and the output compression data stream. The implementation compresses one sample every clock cycle, which results in a speed of 33 Msample/s. The implementation has a rather low device use of the Xilinx Virtex IV LX25, making the total power consumption of the implementation about 1.27 W.
Annealed Importance Sampling Reversible Jump MCMC algorithms
DOE Office of Scientific and Technical Information (OSTI.GOV)
Karagiannis, Georgios; Andrieu, Christophe
2013-03-20
It will soon be 20 years since reversible jump Markov chain Monte Carlo (RJ-MCMC) algorithms have been proposed. They have significantly extended the scope of Markov chain Monte Carlo simulation methods, offering the promise to be able to routinely tackle transdimensional sampling problems, as encountered in Bayesian model selection problems for example, in a principled and flexible fashion. Their practical efficient implementation, however, still remains a challenge. A particular difficulty encountered in practice is in the choice of the dimension matching variables (both their nature and their distribution) and the reversible transformations which allow one to define the one-to-one mappingsmore » underpinning the design of these algorithms. Indeed, even seemingly sensible choices can lead to algorithms with very poor performance. The focus of this paper is the development and performance evaluation of a method, annealed importance sampling RJ-MCMC (aisRJ), which addresses this problem by mitigating the sensitivity of RJ-MCMC algorithms to the aforementioned poor design. As we shall see the algorithm can be understood as being an “exact approximation” of an idealized MCMC algorithm that would sample from the model probabilities directly in a model selection set-up. Such an idealized algorithm may have good theoretical convergence properties, but typically cannot be implemented, and our algorithms can approximate the performance of such idealized algorithms to an arbitrary degree while not introducing any bias for any degree of approximation. Our approach combines the dimension matching ideas of RJ-MCMC with annealed importance sampling and its Markov chain Monte Carlo implementation. We illustrate the performance of the algorithm with numerical simulations which indicate that, although the approach may at first appear computationally involved, it is in fact competitive.« less
NASA Astrophysics Data System (ADS)
Zackay, Barak; Ofek, Eran O.
2017-01-01
Astronomical radio signals are subjected to phase dispersion while traveling through the interstellar medium. To optimally detect a short-duration signal within a frequency band, we have to precisely compensate for the unknown pulse dispersion, which is a computationally demanding task. We present the “fast dispersion measure transform” algorithm for optimal detection of such signals. Our algorithm has a low theoretical complexity of 2{N}f{N}t+{N}t{N}{{Δ }}{{log}}2({N}f), where Nf, Nt, and NΔ are the numbers of frequency bins, time bins, and dispersion measure bins, respectively. Unlike previously suggested fast algorithms, our algorithm conserves the sensitivity of brute-force dedispersion. Our tests indicate that this algorithm, running on a standard desktop computer and implemented in a high-level programming language, is already faster than the state-of-the-art dedispersion codes running on graphical processing units (GPUs). We also present a variant of the algorithm that can be efficiently implemented on GPUs. The latter algorithm’s computation and data-transport requirements are similar to those of a two-dimensional fast Fourier transform, indicating that incoherent dedispersion can now be considered a nonissue while planning future surveys. We further present a fast algorithm for sensitive detection of pulses shorter than the dispersive smearing limits of incoherent dedispersion. In typical cases, this algorithm is orders of magnitude faster than enumerating dispersion measures and coherently dedispersing by convolution. We analyze the computational complexity of pulsed signal searches by radio interferometers. We conclude that, using our suggested algorithms, maximally sensitive blind searches for dispersed pulses are feasible using existing facilities. We provide an implementation of these algorithms in Python and MATLAB.
Fast algorithm for computing complex number-theoretic transforms
NASA Technical Reports Server (NTRS)
Reed, I. S.; Liu, K. Y.; Truong, T. K.
1977-01-01
A high-radix FFT algorithm for computing transforms over FFT, where q is a Mersenne prime, is developed to implement fast circular convolutions. This new algorithm requires substantially fewer multiplications than the conventional FFT.
Real-time implementation of a multispectral mine target detection algorithm
NASA Astrophysics Data System (ADS)
Samson, Joseph W.; Witter, Lester J.; Kenton, Arthur C.; Holloway, John H., Jr.
2003-09-01
Spatial-spectral anomaly detection (the "RX Algorithm") has been exploited on the USMC's Coastal Battlefield Reconnaissance and Analysis (COBRA) Advanced Technology Demonstration (ATD) and several associated technology base studies, and has been found to be a useful method for the automated detection of surface-emplaced antitank land mines in airborne multispectral imagery. RX is a complex image processing algorithm that involves the direct spatial convolution of a target/background mask template over each multispectral image, coupled with a spatially variant background spectral covariance matrix estimation and inversion. The RX throughput on the ATD was about 38X real time using a single Sun UltraSparc system. A goal to demonstrate RX in real-time was begun in FY01. We now report the development and demonstration of a Field Programmable Gate Array (FPGA) solution that achieves a real-time implementation of the RX algorithm at video rates using COBRA ATD data. The approach uses an Annapolis Microsystems Firebird PMC card containing a Xilinx XCV2000E FPGA with over 2,500,000 logic gates and 18MBytes of memory. A prototype system was configured using a Tek Microsystems VME board with dual-PowerPC G4 processors and two PMC slots. The RX algorithm was translated from its C programming implementation into the VHDL language and synthesized into gates that were loaded into the FPGA. The VHDL/synthesizer approach allows key RX parameters to be quickly changed and a new implementation automatically generated. Reprogramming the FPGA is done rapidly and in-circuit. Implementation of the RX algorithm in a single FPGA is a major first step toward achieving real-time land mine detection.
Computing the Density Matrix in Electronic Structure Theory on Graphics Processing Units.
Cawkwell, M J; Sanville, E J; Mniszewski, S M; Niklasson, Anders M N
2012-11-13
The self-consistent solution of a Schrödinger-like equation for the density matrix is a critical and computationally demanding step in quantum-based models of interatomic bonding. This step was tackled historically via the diagonalization of the Hamiltonian. We have investigated the performance and accuracy of the second-order spectral projection (SP2) algorithm for the computation of the density matrix via a recursive expansion of the Fermi operator in a series of generalized matrix-matrix multiplications. We demonstrate that owing to its simplicity, the SP2 algorithm [Niklasson, A. M. N. Phys. Rev. B2002, 66, 155115] is exceptionally well suited to implementation on graphics processing units (GPUs). The performance in double and single precision arithmetic of a hybrid GPU/central processing unit (CPU) and full GPU implementation of the SP2 algorithm exceed those of a CPU-only implementation of the SP2 algorithm and traditional matrix diagonalization when the dimensions of the matrices exceed about 2000 × 2000. Padding schemes for arrays allocated in the GPU memory that optimize the performance of the CUBLAS implementations of the level 3 BLAS DGEMM and SGEMM subroutines for generalized matrix-matrix multiplications are described in detail. The analysis of the relative performance of the hybrid CPU/GPU and full GPU implementations indicate that the transfer of arrays between the GPU and CPU constitutes only a small fraction of the total computation time. The errors measured in the self-consistent density matrices computed using the SP2 algorithm are generally smaller than those measured in matrices computed via diagonalization. Furthermore, the errors in the density matrices computed using the SP2 algorithm do not exhibit any dependence of system size, whereas the errors increase linearly with the number of orbitals when diagonalization is employed.
Mitra, Avik; Ghosh, Arindam; Das, Ranabir; Patel, Apoorva; Kumar, Anil
2005-12-01
Quantum adiabatic algorithm is a method of solving computational problems by evolving the ground state of a slowly varying Hamiltonian. The technique uses evolution of the ground state of a slowly varying Hamiltonian to reach the required output state. In some cases, such as the adiabatic versions of Grover's search algorithm and Deutsch-Jozsa algorithm, applying the global adiabatic evolution yields a complexity similar to their classical algorithms. However, using the local adiabatic evolution, the algorithms given by J. Roland and N.J. Cerf for Grover's search [J. Roland, N.J. Cerf, Quantum search by local adiabatic evolution, Phys. Rev. A 65 (2002) 042308] and by Saurya Das, Randy Kobes, and Gabor Kunstatter for the Deutsch-Jozsa algorithm [S. Das, R. Kobes, G. Kunstatter, Adiabatic quantum computation and Deutsh's algorithm, Phys. Rev. A 65 (2002) 062301], yield a complexity of order N (where N=2(n) and n is the number of qubits). In this paper, we report the experimental implementation of these local adiabatic evolution algorithms on a 2-qubit quantum information processor, by Nuclear Magnetic Resonance.
NASA Astrophysics Data System (ADS)
Ham, Woonchul; Song, Chulgyu
2017-05-01
In this paper, we propose a new three-dimensional stereo image reconstruction algorithm for a photoacoustic medical imaging system. We also introduce and discuss a new theoretical algorithm by using the physical concept of Radon transform. The main key concept of proposed theoretical algorithm is to evaluate the existence possibility of the acoustic source within a searching region by using the geometric distance between each sensor element of acoustic detector and the corresponding searching region denoted by grid. We derive the mathematical equation for the magnitude of the existence possibility which can be used for implementing a new proposed algorithm. We handle and derive mathematical equations of proposed algorithm for the one-dimensional sensing array case as well as two dimensional sensing array case too. A mathematical k-wave simulation data are used for comparing the image quality of the proposed algorithm with that of general conventional algorithm in which the FFT should be necessarily used. From the k-wave Matlab simulation results, we can prove the effectiveness of the proposed reconstruction algorithm.
An implementation of a data-transmission pipelining algorithm on Imote2 platforms
NASA Astrophysics Data System (ADS)
Li, Xu; Dorvash, Siavash; Cheng, Liang; Pakzad, Shamim
2011-04-01
Over the past several years, wireless network systems and sensing technologies have been developed significantly. This has resulted in the broad application of wireless sensor networks (WSNs) in many engineering fields and in particular structural health monitoring (SHM). The movement of traditional SHM toward the new generation of SHM, which utilizes WSNs, relies on the advantages of this new approach such as relatively low costs, ease of implementation and the capability of onboard data processing and management. In the particular case of long span bridge monitoring, a WSN should be capable of transmitting commands and measurement data over long network geometry in a reliable manner. While using single-hop data transmission in such geometry requires a long radio range and consequently a high level of power supply, multi-hop communication may offer an effective and reliable way for data transmissions across the network. Using a multi-hop communication protocol, the network relays data from a remote node to the base station via intermediary nodes. We have proposed a data-transmission pipelining algorithm to enable an effective use of the available bandwidth and minimize the energy consumption and the delay performance by the multi-hop communication protocol. This paper focuses on the implementation aspect of the pipelining algorithm on Imote2 platforms for SHM applications, describes its interaction with underlying routing protocols, and presents the solutions to various implementation issues of the proposed pipelining algorithm. Finally, the performance of the algorithm is evaluated based on the results of an experimental implementation.
Abid, Abdulbasit
2013-03-01
This paper presents a thorough discussion of the proposed field-programmable gate array (FPGA) implementation for fringe pattern demodulation using the one-dimensional continuous wavelet transform (1D-CWT) algorithm. This algorithm is also known as wavelet transform profilometry. Initially, the 1D-CWT is programmed using the C programming language and compiled into VHDL using the ImpulseC tool. This VHDL code is implemented on the Altera Cyclone IV GX EP4CGX150DF31C7 FPGA. A fringe pattern image with a size of 512×512 pixels is presented to the FPGA, which processes the image using the 1D-CWT algorithm. The FPGA requires approximately 100 ms to process the image and produce a wrapped phase map. For performance comparison purposes, the 1D-CWT algorithm is programmed using the C language. The C code is then compiled using the Intel compiler version 13.0. The compiled code is run on a Dell Precision state-of-the-art workstation. The time required to process the fringe pattern image is approximately 1 s. In order to further reduce the execution time, the 1D-CWT is reprogramed using Intel Integrated Primitive Performance (IPP) Library Version 7.1. The execution time was reduced to approximately 650 ms. This confirms that at least sixfold speedup was gained using FPGA implementation over a state-of-the-art workstation that executes heavily optimized implementation of the 1D-CWT algorithm.
NASA Astrophysics Data System (ADS)
Akil, Mohamed
2017-05-01
The real-time processing is getting more and more important in many image processing applications. Image segmentation is one of the most fundamental tasks image analysis. As a consequence, many different approaches for image segmentation have been proposed. The watershed transform is a well-known image segmentation tool. The watershed transform is a very data intensive task. To achieve acceleration and obtain real-time processing of watershed algorithms, parallel architectures and programming models for multicore computing have been developed. This paper focuses on the survey of the approaches for parallel implementation of sequential watershed algorithms on multicore general purpose CPUs: homogeneous multicore processor with shared memory. To achieve an efficient parallel implementation, it's necessary to explore different strategies (parallelization/distribution/distributed scheduling) combined with different acceleration and optimization techniques to enhance parallelism. In this paper, we give a comparison of various parallelization of sequential watershed algorithms on shared memory multicore architecture. We analyze the performance measurements of each parallel implementation and the impact of the different sources of overhead on the performance of the parallel implementations. In this comparison study, we also discuss the advantages and disadvantages of the parallel programming models. Thus, we compare the OpenMP (an application programming interface for multi-Processing) with Ptheads (POSIX Threads) to illustrate the impact of each parallel programming model on the performance of the parallel implementations.
NASA Astrophysics Data System (ADS)
García-Flores, Agustín.; Paz-Gallardo, Abel; Plaza, Antonio; Li, Jun
2016-10-01
This paper describes a new web platform dedicated to the classification of satellite images called Hypergim. The current implementation of this platform enables users to perform classification of satellite images from any part of the world thanks to the worldwide maps provided by Google Maps. To perform this classification, Hypergim uses unsupervised algorithms like Isodata and K-means. Here, we present an extension of the original platform in which we adapt Hypergim in order to use supervised algorithms to improve the classification results. This involves a significant modification of the user interface, providing the user with a way to obtain samples of classes present in the images to use in the training phase of the classification process. Another main goal of this development is to improve the runtime of the image classification process. To achieve this goal, we use a parallel implementation of the Random Forest classification algorithm. This implementation is a modification of the well-known CURFIL software package. The use of this type of algorithms to perform image classification is widespread today thanks to its precision and ease of training. The actual implementation of Random Forest was developed using CUDA platform, which enables us to exploit the potential of several models of NVIDIA graphics processing units using them to execute general purpose computing tasks as image classification algorithms. As well as CUDA, we use other parallel libraries as Intel Boost, taking advantage of the multithreading capabilities of modern CPUs. To ensure the best possible results, the platform is deployed in a cluster of commodity graphics processing units (GPUs), so that multiple users can use the tool in a concurrent way. The experimental results indicate that this new algorithm widely outperform the previous unsupervised algorithms implemented in Hypergim, both in runtime as well as precision of the actual classification of the images.
Efficient Hardware Implementation of the Lightweight Block Encryption Algorithm LEA
Lee, Donggeon; Kim, Dong-Chan; Kwon, Daesung; Kim, Howon
2014-01-01
Recently, due to the advent of resource-constrained trends, such as smartphones and smart devices, the computing environment is changing. Because our daily life is deeply intertwined with ubiquitous networks, the importance of security is growing. A lightweight encryption algorithm is essential for secure communication between these kinds of resource-constrained devices, and many researchers have been investigating this field. Recently, a lightweight block cipher called LEA was proposed. LEA was originally targeted for efficient implementation on microprocessors, as it is fast when implemented in software and furthermore, it has a small memory footprint. To reflect on recent technology, all required calculations utilize 32-bit wide operations. In addition, the algorithm is comprised of not complex S-Box-like structures but simple Addition, Rotation, and XOR operations. To the best of our knowledge, this paper is the first report on a comprehensive hardware implementation of LEA. We present various hardware structures and their implementation results according to key sizes. Even though LEA was originally targeted at software efficiency, it also shows high efficiency when implemented as hardware. PMID:24406859
FPGA implementation of sparse matrix algorithm for information retrieval
NASA Astrophysics Data System (ADS)
Bojanic, Slobodan; Jevtic, Ruzica; Nieto-Taladriz, Octavio
2005-06-01
Information text data retrieval requires a tremendous amount of processing time because of the size of the data and the complexity of information retrieval algorithms. In this paper the solution to this problem is proposed via hardware supported information retrieval algorithms. Reconfigurable computing may adopt frequent hardware modifications through its tailorable hardware and exploits parallelism for a given application through reconfigurable and flexible hardware units. The degree of the parallelism can be tuned for data. In this work we implemented standard BLAS (basic linear algebra subprogram) sparse matrix algorithm named Compressed Sparse Row (CSR) that is showed to be more efficient in terms of storage space requirement and query-processing timing over the other sparse matrix algorithms for information retrieval application. Although inverted index algorithm is treated as the de facto standard for information retrieval for years, an alternative approach to store the index of text collection in a sparse matrix structure gains more attention. This approach performs query processing using sparse matrix-vector multiplication and due to parallelization achieves a substantial efficiency over the sequential inverted index. The parallel implementations of information retrieval kernel are presented in this work targeting the Virtex II Field Programmable Gate Arrays (FPGAs) board from Xilinx. A recent development in scientific applications is the use of FPGA to achieve high performance results. Computational results are compared to implementations on other platforms. The design achieves a high level of parallelism for the overall function while retaining highly optimised hardware within processing unit.
RACER: Effective Race Detection Using AspectJ
NASA Technical Reports Server (NTRS)
Bodden, Eric; Havelund, Klaus
2008-01-01
The limits of coding with joint constraints on detected and undetected error rates Programming errors occur frequently in large software systems, and even more so if these systems are concurrent. In the past, researchers have developed specialized programs to aid programmers detecting concurrent programming errors such as deadlocks, livelocks, starvation and data races. In this work we propose a language extension to the aspect-oriented programming language AspectJ, in the form of three new built-in pointcuts, lock(), unlock() and may be Shared(), which allow programmers to monitor program events where locks are granted or handed back, and where values are accessed that may be shared amongst multiple Java threads. We decide thread-locality using a static thread-local objects analysis developed by others. Using the three new primitive pointcuts, researchers can directly implement efficient monitoring algorithms to detect concurrent programming errors online. As an example, we expose a new algorithm which we call RACER, an adoption of the well-known ERASER algorithm to the memory model of Java. We implemented the new pointcuts as an extension to the Aspect Bench Compiler, implemented the RACER algorithm using this language extension and then applied the algorithm to the NASA K9 Rover Executive. Our experiments proved our implementation very effective. In the Rover Executive RACER finds 70 data races. Only one of these races was previously known.We further applied the algorithm to two other multi-threaded programs written by Computer Science researchers, in which we found races as well.
Proof of a new colour decomposition for QCD amplitudes
Melia, Tom
2015-12-16
Recently, Johansson and Ochirov conjectured the form of a new colour decom-position for QCD tree-level amplitudes. This note provides a proof of that conjecture. The proof is based on ‘Mario World’ Feynman diagrams, which exhibit the hierarchical Dyck structure previously found to be very useful when dealing with multi-quark amplitudes.
Zanderighi, Giulia
2018-04-26
Modern QCD - Lecture 1 Starting from the QCD Lagrangian we will revisit some basic QCD concepts and derive fundamental properties like gauge invariance and isospin symmetry and will discuss the Feynman rules of the theory. We will then focus on the gauge group of QCD and derive the Casimirs CF and CA and some useful color identities.
Differential equations for loop integrals in Baikov representation
NASA Astrophysics Data System (ADS)
Bosma, Jorrit; Larsen, Kasper J.; Zhang, Yang
2018-05-01
We present a proof that differential equations for Feynman loop integrals can always be derived in Baikov representation without involving dimension-shift identities. We moreover show that in a large class of two- and three-loop diagrams it is possible to avoid squared propagators in the intermediate steps of setting up the differential equations.
Exotic Gauge Bosons in the 331 Model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Romero, D.; Ravinez, O.; Diaz, H.
We analize the bosonic sector of the 331 model which contains exotic leptons, quarks and bosons (E,J,U,V) in order to satisfy the weak gauge SU(3){sub L} invariance. We develop the Feynman rules of the entire kinetic bosonic sector which will let us to compute some of the Z(0)' decays modes.
Using and Applying Mathematics
ERIC Educational Resources Information Center
Knight, Rupert
2011-01-01
The Nobel prize winning physicist Richard Feynman (2007) famously enthused about "the pleasure of finding things out". In day-to-day classroom life, however, it is easy to lose and undervalue this pleasure in the process, as opposed to products, of mathematics. Finding things out involves a journey and is often where the learning takes place.…
Loopedia, a database for loop integrals
NASA Astrophysics Data System (ADS)
Bogner, C.; Borowka, S.; Hahn, T.; Heinrich, G.; Jones, S. P.; Kerner, M.; von Manteuffel, A.; Michel, M.; Panzer, E.; Papara, V.
2018-04-01
Loopedia is a new database at loopedia.org for information on Feynman integrals, intended to provide both bibliographic information as well as results made available by the community. Its bibliometry is complementary to that of INSPIRE or arXiv in the sense that it admits searching for integrals by graph-theoretical objects, e.g. its topology.
Methods and Strategies: Much Ado about Nothing
ERIC Educational Resources Information Center
Smith, P. Sean; Plumley, Courtney L.; Hayes, Meredith L.
2017-01-01
This column provides ideas and techniques to enhance your science teaching. This month's issue discusses how children think about the small-particle model of matter. What Richard Feynman referred to as the "atomic hypothesis" is perhaps more familiar to us as the small-particle model of matter. In its most basic form, the model states…
ERIC Educational Resources Information Center
Hecht, Eugene
2007-01-01
When Feynman wrote, "It is important to realize that in physics today, we have no knowledge of what energy is," he was recognizing that although we have expressions for various forms of energy from kinetic to elastic, we seem to have no idea of what the all-encompassing notion of "energy" "is": This paper addresses that issue offering a definition…
NASA Astrophysics Data System (ADS)
Clegg, Brian
2018-04-01
Everybody knows that quantum physics is weird, right? Indeed, quantum physicist Richard Feynman once said in a lecture: "The theory of quantum electrodynamics describes Nature as absurd from the point of view of common sense." Beyond Weird: Why Everything You Thought You Knew About Quantum Physics is Different by Philip Ball presents a refreshing challenge to this viewpoint.
Path Integration on the Upper Half-Plane
NASA Astrophysics Data System (ADS)
Kubo, R.
1987-10-01
Feynman's path integral is considered on the Poincaré upper half-plane. It is shown that the fundermental solution to the heat equation partial f/partial t=Delta_{H}f can be expressed in terms of a path integral. A simple relation between the path integral and the Selberg trace formula is discussed briefly.
Proof of a new colour decomposition for QCD amplitudes
DOE Office of Scientific and Technical Information (OSTI.GOV)
Melia, Tom
Recently, Johansson and Ochirov conjectured the form of a new colour decom-position for QCD tree-level amplitudes. This note provides a proof of that conjecture. The proof is based on ‘Mario World’ Feynman diagrams, which exhibit the hierarchical Dyck structure previously found to be very useful when dealing with multi-quark amplitudes.
Quantum space foam and string theory
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nekrasov, Nikita
2006-11-03
String theory is originally defined as a modification of the Feynman rules in perturbation theory. It contains gravity in its perturbative spectrum. We review some recent developments which demonstrate that nonperturbative effects of quantum gravity, such as spacetime foam, arise in string theory as well.Prepared for the proceedings of 'Albert Einstein Century Conference' , Paris July 2005.
NASA Astrophysics Data System (ADS)
Vlasiuk, Maryna; Frascoli, Federico; Sadus, Richard J.
2016-09-01
The thermodynamic, structural, and vapor-liquid equilibrium properties of neon are comprehensively studied using ab initio, empirical, and semi-classical intermolecular potentials and classical Monte Carlo simulations. Path integral Monte Carlo simulations for isochoric heat capacity and structural properties are also reported for two empirical potentials and one ab initio potential. The isobaric and isochoric heat capacities, thermal expansion coefficient, thermal pressure coefficient, isothermal and adiabatic compressibilities, Joule-Thomson coefficient, and the speed of sound are reported and compared with experimental data for the entire range of liquid densities from the triple point to the critical point. Lustig's thermodynamic approach is formally extended for temperature-dependent intermolecular potentials. Quantum effects are incorporated using the Feynman-Hibbs quantum correction, which results in significant improvement in the accuracy of predicted thermodynamic properties. The new Feynman-Hibbs version of the Hellmann-Bich-Vogel potential predicts the isochoric heat capacity to an accuracy of 1.4% over the entire range of liquid densities. It also predicts other thermodynamic properties more accurately than alternative intermolecular potentials.
Possible Quantum Absorber Effects in Cortical Synchronization
NASA Astrophysics Data System (ADS)
Kämpf, Uwe
The Wheeler-Feynman transactional "absorber" approach was proposed originally to account for anomalous resonance coupling between spatio-temporally distant measurement partners in entangled quantum states of so-called Einstein-Podolsky-Rosen paradoxes, e.g. of spatio-temporal non-locality, quantum teleportation, etc. Applied to quantum brain dynamics, however, this view provides an anticipative resonance coupling model for aspects of cortical synchronization and recurrent visual action control. It is proposed to consider the registered activation patterns of neuronal loops in so-called synfire chains not as a result of retarded brain communication processes, but rather as surface effects of a system of standing waves generated in the depth of visual processing. According to this view, they arise from a counterbalance between the actual input's delayed bottom-up data streams and top-down recurrent information-processing of advanced anticipative signals in a Wheeler-Feynman-type absorber mode. In the framework of a "time-loop" model, findings about mirror neurons in the brain cortex are suggested to be at least partially associated with temporal rather than spatial mirror functions of visual processing, similar to phase conjugate adaptive resonance-coupling in nonlinear optics.
Automatic Whistler Detector and Analyzer system: Implementation of the analyzer algorithm
NASA Astrophysics Data System (ADS)
Lichtenberger, JáNos; Ferencz, Csaba; Hamar, Daniel; Steinbach, Peter; Rodger, Craig J.; Clilverd, Mark A.; Collier, Andrew B.
2010-12-01
The full potential of whistlers for monitoring plasmaspheric electron density variations has not yet been realized. The primary reason is the vast human effort required for the analysis of whistler traces. Recently, the first part of a complete whistler analysis procedure was successfully automated, i.e., the automatic detection of whistler traces from the raw broadband VLF signal was achieved. This study describes a new algorithm developed to determine plasmaspheric electron density measurements from whistler traces, based on a Virtual (Whistler) Trace Transformation, using a 2-D fast Fourier transform transformation. This algorithm can be automated and can thus form the final step to complete an Automatic Whistler Detector and Analyzer (AWDA) system. In this second AWDA paper, the practical implementation of the Automatic Whistler Analyzer (AWA) algorithm is discussed and a feasible solution is presented. The practical implementation of the algorithm is able to track the variations of plasmasphere in quasi real time on a PC cluster with 100 CPU cores. The electron densities obtained by the AWA method can be used in investigations such as plasmasphere dynamics, ionosphere-plasmasphere coupling, or in space weather models.
Improving serum calcium test ordering according to a decision algorithm.
Faria, Daniel K; Taniguchi, Leandro U; Fonseca, Luiz A M; Ferreira-Junior, Mario; Aguiar, Francisco J B; Lichtenstein, Arnaldo; Sumita, Nairo M; Duarte, Alberto J S; Sales, Maria M
2018-05-18
To detect differences in the pattern of serum calcium tests ordering before and after the implementation of a decision algorithm. We studied patients admitted to an internal medicine ward of a university hospital on April 2013 and April 2016. Patients were classified as critical or non-critical on the day when each test was performed. Adequacy of ordering was defined according to adherence to a decision algorithm implemented in 2014. Total and ionised calcium tests per patient-day of hospitalisation significantly decreased after the algorithm implementation; and duplication of tests (total and ionised calcium measured in the same blood sample) was reduced by 49%. Overall adequacy of ionised calcium determinations increased by 23% (P=0.0001) due to the increase in the adequacy of ionised calcium ordering in non-critical conditions. A decision algorithm can be a useful educational tool to improve adequacy of the process of ordering serum calcium tests. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Scemama, Anthony; Renon, Nicolas; Rapacioli, Mathias
2014-06-10
We present an algorithm and its parallel implementation for solving a self-consistent problem as encountered in Hartree-Fock or density functional theory. The algorithm takes advantage of the sparsity of matrices through the use of local molecular orbitals. The implementation allows one to exploit efficiently modern symmetric multiprocessing (SMP) computer architectures. As a first application, the algorithm is used within the density-functional-based tight binding method, for which most of the computational time is spent in the linear algebra routines (diagonalization of the Fock/Kohn-Sham matrix). We show that with this algorithm (i) single point calculations on very large systems (millions of atoms) can be performed on large SMP machines, (ii) calculations involving intermediate size systems (1000-100 000 atoms) are also strongly accelerated and can run efficiently on standard servers, and (iii) the error on the total energy due to the use of a cutoff in the molecular orbital coefficients can be controlled such that it remains smaller than the SCF convergence criterion.
Implementation of a parallel protein structure alignment service on cloud.
Hung, Che-Lun; Lin, Yaw-Ling
2013-01-01
Protein structure alignment has become an important strategy by which to identify evolutionary relationships between protein sequences. Several alignment tools are currently available for online comparison of protein structures. In this paper, we propose a parallel protein structure alignment service based on the Hadoop distribution framework. This service includes a protein structure alignment algorithm, a refinement algorithm, and a MapReduce programming model. The refinement algorithm refines the result of alignment. To process vast numbers of protein structures in parallel, the alignment and refinement algorithms are implemented using MapReduce. We analyzed and compared the structure alignments produced by different methods using a dataset randomly selected from the PDB database. The experimental results verify that the proposed algorithm refines the resulting alignments more accurately than existing algorithms. Meanwhile, the computational performance of the proposed service is proportional to the number of processors used in our cloud platform.
Implementation of a Parallel Protein Structure Alignment Service on Cloud
Hung, Che-Lun; Lin, Yaw-Ling
2013-01-01
Protein structure alignment has become an important strategy by which to identify evolutionary relationships between protein sequences. Several alignment tools are currently available for online comparison of protein structures. In this paper, we propose a parallel protein structure alignment service based on the Hadoop distribution framework. This service includes a protein structure alignment algorithm, a refinement algorithm, and a MapReduce programming model. The refinement algorithm refines the result of alignment. To process vast numbers of protein structures in parallel, the alignment and refinement algorithms are implemented using MapReduce. We analyzed and compared the structure alignments produced by different methods using a dataset randomly selected from the PDB database. The experimental results verify that the proposed algorithm refines the resulting alignments more accurately than existing algorithms. Meanwhile, the computational performance of the proposed service is proportional to the number of processors used in our cloud platform. PMID:23671842
An efficient quantum algorithm for spectral estimation
NASA Astrophysics Data System (ADS)
Steffens, Adrian; Rebentrost, Patrick; Marvian, Iman; Eisert, Jens; Lloyd, Seth
2017-03-01
We develop an efficient quantum implementation of an important signal processing algorithm for line spectral estimation: the matrix pencil method, which determines the frequencies and damping factors of signals consisting of finite sums of exponentially damped sinusoids. Our algorithm provides a quantum speedup in a natural regime where the sampling rate is much higher than the number of sinusoid components. Along the way, we develop techniques that are expected to be useful for other quantum algorithms as well—consecutive phase estimations to efficiently make products of asymmetric low rank matrices classically accessible and an alternative method to efficiently exponentiate non-Hermitian matrices. Our algorithm features an efficient quantum-classical division of labor: the time-critical steps are implemented in quantum superposition, while an interjacent step, requiring much fewer parameters, can operate classically. We show that frequencies and damping factors can be obtained in time logarithmic in the number of sampling points, exponentially faster than known classical algorithms.
Cavity control as a new quantum algorithms implementation treatment
NASA Astrophysics Data System (ADS)
AbuGhanem, M.; Homid, A. H.; Abdel-Aty, M.
2018-02-01
Based on recent experiments [ Nature 449, 438 (2007) and Nature Physics 6, 777 (2010)], a new approach for realizing quantum gates for the design of quantum algorithms was developed. Accordingly, the operation times of such gates while functioning in algorithm applications depend on the number of photons present in their resonant cavities. Multi-qubit algorithms can be realized in systems in which the photon number is increased slightly over the qubit number. In addition, the time required for operation is considerably less than the dephasing and relaxation times of the systems. The contextual use of the photon number as a main control in the realization of any algorithm was demonstrated. The results indicate the possibility of a full integration into the realization of multi-qubit multiphoton states and its application in algorithm designs. Furthermore, this approach will lead to a successful implementation of these designs in future experiments.
Systolic array processing of the sequential decoding algorithm
NASA Technical Reports Server (NTRS)
Chang, C. Y.; Yao, K.
1989-01-01
A systolic array processing technique is applied to implementing the stack algorithm form of the sequential decoding algorithm. It is shown that sorting, a key function in the stack algorithm, can be efficiently realized by a special type of systolic arrays known as systolic priority queues. Compared to the stack-bucket algorithm, this approach is shown to have the advantages that the decoding always moves along the optimal path, that it has a fast and constant decoding speed and that its simple and regular hardware architecture is suitable for VLSI implementation. Three types of systolic priority queues are discussed: random access scheme, shift register scheme and ripple register scheme. The property of the entries stored in the systolic priority queue is also investigated. The results are applicable to many other basic sorting type problems.
Canbay, Ferhat; Levent, Vecdi Emre; Serbes, Gorkem; Ugurdag, H. Fatih; Goren, Sezer
2016-01-01
The authors aimed to develop an application for producing different architectures to implement dual tree complex wavelet transform (DTCWT) having near shift-invariance property. To obtain a low-cost and portable solution for implementing the DTCWT in multi-channel real-time applications, various embedded-system approaches are realised. For comparison, the DTCWT was implemented in C language on a personal computer and on a PIC microcontroller. However, in the former approach portability and in the latter desired speed performance properties cannot be achieved. Hence, implementation of the DTCWT on a reconfigurable platform such as field programmable gate array, which provides portable, low-cost, low-power, and high-performance computing, is considered as the most feasible solution. At first, they used the system generator DSP design tool of Xilinx for algorithm design. However, the design implemented by using such tools is not optimised in terms of area and power. To overcome all these drawbacks mentioned above, they implemented the DTCWT algorithm by using Verilog Hardware Description Language, which has its own difficulties. To overcome these difficulties, simplify the usage of proposed algorithms and the adaptation procedures, a code generator program that can produce different architectures is proposed. PMID:27733925
Canbay, Ferhat; Levent, Vecdi Emre; Serbes, Gorkem; Ugurdag, H Fatih; Goren, Sezer; Aydin, Nizamettin
2016-09-01
The authors aimed to develop an application for producing different architectures to implement dual tree complex wavelet transform (DTCWT) having near shift-invariance property. To obtain a low-cost and portable solution for implementing the DTCWT in multi-channel real-time applications, various embedded-system approaches are realised. For comparison, the DTCWT was implemented in C language on a personal computer and on a PIC microcontroller. However, in the former approach portability and in the latter desired speed performance properties cannot be achieved. Hence, implementation of the DTCWT on a reconfigurable platform such as field programmable gate array, which provides portable, low-cost, low-power, and high-performance computing, is considered as the most feasible solution. At first, they used the system generator DSP design tool of Xilinx for algorithm design. However, the design implemented by using such tools is not optimised in terms of area and power. To overcome all these drawbacks mentioned above, they implemented the DTCWT algorithm by using Verilog Hardware Description Language, which has its own difficulties. To overcome these difficulties, simplify the usage of proposed algorithms and the adaptation procedures, a code generator program that can produce different architectures is proposed.
Parallel heterogeneous architectures for efficient OMP compressive sensing reconstruction
NASA Astrophysics Data System (ADS)
Kulkarni, Amey; Stanislaus, Jerome L.; Mohsenin, Tinoosh
2014-05-01
Compressive Sensing (CS) is a novel scheme, in which a signal that is sparse in a known transform domain can be reconstructed using fewer samples. The signal reconstruction techniques are computationally intensive and have sluggish performance, which make them impractical for real-time processing applications . The paper presents novel architectures for Orthogonal Matching Pursuit algorithm, one of the popular CS reconstruction algorithms. We show the implementation results of proposed architectures on FPGA, ASIC and on a custom many-core platform. For FPGA and ASIC implementation, a novel thresholding method is used to reduce the processing time for the optimization problem by at least 25%. Whereas, for the custom many-core platform, efficient parallelization techniques are applied, to reconstruct signals with variant signal lengths of N and sparsity of m. The algorithm is divided into three kernels. Each kernel is parallelized to reduce execution time, whereas efficient reuse of the matrix operators allows us to reduce area. Matrix operations are efficiently paralellized by taking advantage of blocked algorithms. For demonstration purpose, all architectures reconstruct a 256-length signal with maximum sparsity of 8 using 64 measurements. Implementation on Xilinx Virtex-5 FPGA, requires 27.14 μs to reconstruct the signal using basic OMP. Whereas, with thresholding method it requires 18 μs. ASIC implementation reconstructs the signal in 13 μs. However, our custom many-core, operating at 1.18 GHz, takes 18.28 μs to complete. Our results show that compared to the previous published work of the same algorithm and matrix size, proposed architectures for FPGA and ASIC implementations perform 1.3x and 1.8x respectively faster. Also, the proposed many-core implementation performs 3000x faster than the CPU and 2000x faster than the GPU.
FUX-Sim: Implementation of a fast universal simulation/reconstruction framework for X-ray systems.
Abella, Monica; Serrano, Estefania; Garcia-Blas, Javier; García, Ines; de Molina, Claudia; Carretero, Jesus; Desco, Manuel
2017-01-01
The availability of digital X-ray detectors, together with advances in reconstruction algorithms, creates an opportunity for bringing 3D capabilities to conventional radiology systems. The downside is that reconstruction algorithms for non-standard acquisition protocols are generally based on iterative approaches that involve a high computational burden. The development of new flexible X-ray systems could benefit from computer simulations, which may enable performance to be checked before expensive real systems are implemented. The development of simulation/reconstruction algorithms in this context poses three main difficulties. First, the algorithms deal with large data volumes and are computationally expensive, thus leading to the need for hardware and software optimizations. Second, these optimizations are limited by the high flexibility required to explore new scanning geometries, including fully configurable positioning of source and detector elements. And third, the evolution of the various hardware setups increases the effort required for maintaining and adapting the implementations to current and future programming models. Previous works lack support for completely flexible geometries and/or compatibility with multiple programming models and platforms. In this paper, we present FUX-Sim, a novel X-ray simulation/reconstruction framework that was designed to be flexible and fast. Optimized implementation for different families of GPUs (CUDA and OpenCL) and multi-core CPUs was achieved thanks to a modularized approach based on a layered architecture and parallel implementation of the algorithms for both architectures. A detailed performance evaluation demonstrates that for different system configurations and hardware platforms, FUX-Sim maximizes performance with the CUDA programming model (5 times faster than other state-of-the-art implementations). Furthermore, the CPU and OpenCL programming models allow FUX-Sim to be executed over a wide range of hardware platforms.
Helaers, Raphaël; Milinkovitch, Michel C
2010-07-15
The development, in the last decade, of stochastic heuristics implemented in robust application softwares has made large phylogeny inference a key step in most comparative studies involving molecular sequences. Still, the choice of a phylogeny inference software is often dictated by a combination of parameters not related to the raw performance of the implemented algorithm(s) but rather by practical issues such as ergonomics and/or the availability of specific functionalities. Here, we present MetaPIGA v2.0, a robust implementation of several stochastic heuristics for large phylogeny inference (under maximum likelihood), including a Simulated Annealing algorithm, a classical Genetic Algorithm, and the Metapopulation Genetic Algorithm (metaGA) together with complex substitution models, discrete Gamma rate heterogeneity, and the possibility to partition data. MetaPIGA v2.0 also implements the Likelihood Ratio Test, the Akaike Information Criterion, and the Bayesian Information Criterion for automated selection of substitution models that best fit the data. Heuristics and substitution models are highly customizable through manual batch files and command line processing. However, MetaPIGA v2.0 also offers an extensive graphical user interface for parameters setting, generating and running batch files, following run progress, and manipulating result trees. MetaPIGA v2.0 uses standard formats for data sets and trees, is platform independent, runs in 32 and 64-bits systems, and takes advantage of multiprocessor and multicore computers. The metaGA resolves the major problem inherent to classical Genetic Algorithms by maintaining high inter-population variation even under strong intra-population selection. Implementation of the metaGA together with additional stochastic heuristics into a single software will allow rigorous optimization of each heuristic as well as a meaningful comparison of performances among these algorithms. MetaPIGA v2.0 gives access both to high customization for the phylogeneticist, as well as to an ergonomic interface and functionalities assisting the non-specialist for sound inference of large phylogenetic trees using nucleotide sequences. MetaPIGA v2.0 and its extensive user-manual are freely available to academics at http://www.metapiga.org.
2010-01-01
Background The development, in the last decade, of stochastic heuristics implemented in robust application softwares has made large phylogeny inference a key step in most comparative studies involving molecular sequences. Still, the choice of a phylogeny inference software is often dictated by a combination of parameters not related to the raw performance of the implemented algorithm(s) but rather by practical issues such as ergonomics and/or the availability of specific functionalities. Results Here, we present MetaPIGA v2.0, a robust implementation of several stochastic heuristics for large phylogeny inference (under maximum likelihood), including a Simulated Annealing algorithm, a classical Genetic Algorithm, and the Metapopulation Genetic Algorithm (metaGA) together with complex substitution models, discrete Gamma rate heterogeneity, and the possibility to partition data. MetaPIGA v2.0 also implements the Likelihood Ratio Test, the Akaike Information Criterion, and the Bayesian Information Criterion for automated selection of substitution models that best fit the data. Heuristics and substitution models are highly customizable through manual batch files and command line processing. However, MetaPIGA v2.0 also offers an extensive graphical user interface for parameters setting, generating and running batch files, following run progress, and manipulating result trees. MetaPIGA v2.0 uses standard formats for data sets and trees, is platform independent, runs in 32 and 64-bits systems, and takes advantage of multiprocessor and multicore computers. Conclusions The metaGA resolves the major problem inherent to classical Genetic Algorithms by maintaining high inter-population variation even under strong intra-population selection. Implementation of the metaGA together with additional stochastic heuristics into a single software will allow rigorous optimization of each heuristic as well as a meaningful comparison of performances among these algorithms. MetaPIGA v2.0 gives access both to high customization for the phylogeneticist, as well as to an ergonomic interface and functionalities assisting the non-specialist for sound inference of large phylogenetic trees using nucleotide sequences. MetaPIGA v2.0 and its extensive user-manual are freely available to academics at http://www.metapiga.org. PMID:20633263
Wognum, S; Heethuis, S E; Rosario, T; Hoogeman, M S; Bel, A
2014-07-01
The spatial accuracy of deformable image registration (DIR) is important in the implementation of image guided adaptive radiotherapy techniques for cancer in the pelvic region. Validation of algorithms is best performed on phantoms with fiducial markers undergoing controlled large deformations. Excised porcine bladders, exhibiting similar filling and voiding behavior as human bladders, provide such an environment. The aim of this study was to determine the spatial accuracy of different DIR algorithms on CT images of ex vivo porcine bladders with radiopaque fiducial markers applied to the outer surface, for a range of bladder volumes, using various accuracy metrics. Five excised porcine bladders with a grid of 30-40 radiopaque fiducial markers attached to the outer wall were suspended inside a water-filled phantom. The bladder was filled with a controlled amount of water with added contrast medium for a range of filling volumes (100-400 ml in steps of 50 ml) using a luer lock syringe, and CT scans were acquired at each filling volume. DIR was performed for each data set, with the 100 ml bladder as the reference image. Six intensity-based algorithms (optical flow or demons-based) implemented in theMATLAB platform DIRART, a b-spline algorithm implemented in the commercial software package VelocityAI, and a structure-based algorithm (Symmetric Thin Plate Spline Robust Point Matching) were validated, using adequate parameter settings according to values previously published. The resulting deformation vector field from each registration was applied to the contoured bladder structures and to the marker coordinates for spatial error calculation. The quality of the algorithms was assessed by comparing the different error metrics across the different algorithms, and by comparing the effect of deformation magnitude (bladder volume difference) per algorithm, using the Independent Samples Kruskal-Wallis test. The authors found good structure accuracy without dependency on bladder volume difference for all but one algorithm, and with the best result for the structure-based algorithm. Spatial accuracy as assessed from marker errors was disappointing for all algorithms, especially for large volume differences, implying that the deformations described by the registration did not represent anatomically correct deformations. The structure-based algorithm performed the best in terms of marker error for the large volume difference (100-400 ml). In general, for the small volume difference (100-150 ml) the algorithms performed relatively similarly. The structure-based algorithm exhibited the best balance in performance between small and large volume differences, and among the intensity-based algorithms, the algorithm implemented in VelocityAI exhibited the best balance. Validation of multiple DIR algorithms on a novel physiological bladder phantom revealed that the structure accuracy was good for most algorithms, but that the spatial accuracy as assessed from markers was low for all algorithms, especially for large deformations. Hence, many of the available algorithms exhibit sufficient accuracy for contour propagation purposes, but possibly not for accurate dose accumulation.
Convergence Rates of Finite Difference Stochastic Approximation Algorithms
2016-06-01
dfferences as gradient approximations. It is shown that the convergence of these algorithms can be accelerated by controlling the implementation of the...descent algorithm, under various updating schemes using finite dfferences as gradient approximations. It is shown that the convergence of these...the Kiefer-Wolfowitz algorithm and the mirror descent algorithm, under various updating schemes using finite differences as gradient approximations. It
Implementing a Multiple Criteria Model Base in Co-Op with a Graphical User Interface Generator
1993-09-23
PROMETHEE ................................ 44 A. THE ALGORITHM S ................................... 44 1. Basic Algorithm of PROMETHEE I and... PROMETHEE II ..... 45 a. Use of the Algorithm in PROMETHEE I ............. 49 b. Use of the Algorithm in PROMETHEE II ............. 50 V 2. Algorithm of... PROMETHEE V ......................... 50 B. SCREEN DESIGNS OF PROMETHEE ...................... 51 1. PROMETHEE I and PROMETHEE II ................... 52 a
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chrisochoides, N.; Sukup, F.
In this paper we present a parallel implementation of the Bowyer-Watson (BW) algorithm using the task-parallel programming model. The BW algorithm constitutes an ideal mesh refinement strategy for implementing a large class of unstructured mesh generation techniques on both sequential and parallel computers, by preventing the need for global mesh refinement. Its implementation on distributed memory multicomputes using the traditional data-parallel model has been proven very inefficient due to excessive synchronization needed among processors. In this paper we demonstrate that with the task-parallel model we can tolerate synchronization costs inherent to data-parallel methods by exploring concurrency in the processor level.more » Our preliminary performance data indicate that the task- parallel approach: (i) is almost four times faster than the existing data-parallel methods, (ii) scales linearly, and (iii) introduces minimum overheads compared to the {open_quotes}best{close_quotes} sequential implementation of the BW algorithm.« less
NASA Astrophysics Data System (ADS)
Das, Ranabir; Kumar, Anil
2004-10-01
Quantum information processing has been effectively demonstrated on a small number of qubits by nuclear magnetic resonance. An important subroutine in any computing is the readout of the output. "Spectral implementation" originally suggested by Z. L. Madi, R. Bruschweiler, and R. R. Ernst [J. Chem. Phys. 109, 10603 (1999)], provides an elegant method of readout with the use of an extra "observer" qubit. At the end of computation, detection of the observer qubit provides the output via the multiplet structure of its spectrum. In spectral implementation by two-dimensional experiment the observer qubit retains the memory of input state during computation, thereby providing correlated information on input and output, in the same spectrum. Spectral implementation of Grover's search algorithm, approximate quantum counting, a modified version of Berstein-Vazirani problem, and Hogg's algorithm are demonstrated here in three- and four-qubit systems.
An Efficient Solution Method for Multibody Systems with Loops Using Multiple Processors
NASA Technical Reports Server (NTRS)
Ghosh, Tushar K.; Nguyen, Luong A.; Quiocho, Leslie J.
2015-01-01
This paper describes a multibody dynamics algorithm formulated for parallel implementation on multiprocessor computing platforms using the divide-and-conquer approach. The system of interest is a general topology of rigid and elastic articulated bodies with or without loops. The algorithm divides the multibody system into a number of smaller sets of bodies in chain or tree structures, called "branches" at convenient joints called "connection points", and uses an Order-N (O (N)) approach to formulate the dynamics of each branch in terms of the unknown spatial connection forces. The equations of motion for the branches, leaving the connection forces as unknowns, are implemented in separate processors in parallel for computational efficiency, and the equations for all the unknown connection forces are synthesized and solved in one or several processors. The performances of two implementations of this divide-and-conquer algorithm in multiple processors are compared with an existing method implemented on a single processor.
Exploiting Multiple Levels of Parallelism in Sparse Matrix-Matrix Multiplication
Azad, Ariful; Ballard, Grey; Buluc, Aydin; ...
2016-11-08
Sparse matrix-matrix multiplication (or SpGEMM) is a key primitive for many high-performance graph algorithms as well as for some linear solvers, such as algebraic multigrid. The scaling of existing parallel implementations of SpGEMM is heavily bound by communication. Even though 3D (or 2.5D) algorithms have been proposed and theoretically analyzed in the flat MPI model on Erdös-Rényi matrices, those algorithms had not been implemented in practice and their complexities had not been analyzed for the general case. In this work, we present the first implementation of the 3D SpGEMM formulation that exploits multiple (intranode and internode) levels of parallelism, achievingmore » significant speedups over the state-of-the-art publicly available codes at all levels of concurrencies. We extensively evaluate our implementation and identify bottlenecks that should be subject to further research.« less
Parallel digital forensics infrastructure.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liebrock, Lorie M.; Duggan, David Patrick
2009-10-01
This report documents the architecture and implementation of a Parallel Digital Forensics infrastructure. This infrastructure is necessary for supporting the design, implementation, and testing of new classes of parallel digital forensics tools. Digital Forensics has become extremely difficult with data sets of one terabyte and larger. The only way to overcome the processing time of these large sets is to identify and develop new parallel algorithms for performing the analysis. To support algorithm research, a flexible base infrastructure is required. A candidate architecture for this base infrastructure was designed, instantiated, and tested by this project, in collaboration with New Mexicomore » Tech. Previous infrastructures were not designed and built specifically for the development and testing of parallel algorithms. With the size of forensics data sets only expected to increase significantly, this type of infrastructure support is necessary for continued research in parallel digital forensics. This report documents the implementation of the parallel digital forensics (PDF) infrastructure architecture and implementation.« less
Further optimization of SeDDaRA blind image deconvolution algorithm and its DSP implementation
NASA Astrophysics Data System (ADS)
Wen, Bo; Zhang, Qiheng; Zhang, Jianlin
2011-11-01
Efficient algorithm for blind image deconvolution and its high-speed implementation is of great value in practice. Further optimization of SeDDaRA is developed, from algorithm structure to numerical calculation methods. The main optimization covers that, the structure's modularization for good implementation feasibility, reducing the data computation and dependency of 2D-FFT/IFFT, and acceleration of power operation by segmented look-up table. Then the Fast SeDDaRA is proposed and specialized for low complexity. As the final implementation, a hardware system of image restoration is conducted by using the multi-DSP parallel processing. Experimental results show that, the processing time and memory demand of Fast SeDDaRA decreases 50% at least; the data throughput of image restoration system is over 7.8Msps. The optimization is proved efficient and feasible, and the Fast SeDDaRA is able to support the real-time application.
Data parallel sorting for particle simulation
NASA Technical Reports Server (NTRS)
Dagum, Leonardo
1992-01-01
Sorting on a parallel architecture is a communications intensive event which can incur a high penalty in applications where it is required. In the case of particle simulation, only integer sorting is necessary, and sequential implementations easily attain the minimum performance bound of O (N) for N particles. Parallel implementations, however, have to cope with the parallel sorting problem which, in addition to incurring a heavy communications cost, can make the minimun performance bound difficult to attain. This paper demonstrates how the sorting problem in a particle simulation can be reduced to a merging problem, and describes an efficient data parallel algorithm to solve this merging problem in a particle simulation. The new algorithm is shown to be optimal under conditions usual for particle simulation, and its fieldwise implementation on the Connection Machine is analyzed in detail. The new algorithm is about four times faster than a fieldwise implementation of radix sort on the Connection Machine.