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Livres sur le sujet « Particle-based method »

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Auteur : Grafiati

Publié le 14 mars 2023

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1

Oñate, Eugenio, et Roger Owen, dir. Particle-Based Methods. Dordrecht : Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-0735-1.

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2

Oñate, Eugenio. Particle-Based Methods : Fundamentals and Applications. Dordrecht : Springer Science+Business Media B.V., 2011.

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3

service), ScienceDirect (Online, dir. Single molecule tools : Super-resolution, particle tracking, multiparameter and force based methods. San Diego, CA : Academic Press/Elsevier, 2010.

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4

Material Point Method : A Continuum-Based Particle Method for Extreme Loading Cases. Elsevier Science & Technology Books, 2016.

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5

Liu, Yan, Xiong Zhang et Zhen Chen. Material Point Method : A Continuum-Based Particle Method for Extreme Loading Cases. Elsevier Science & Technology, 2016.

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6

Bao, Yun, Carl Chiarella et Boda Kang. Particle Filters for Markov-Switching Stochastic Volatility Models. Sous la direction de Shu-Heng Chen, Mak Kaboudan et Ye-Rong Du. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199844371.013.9.

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This chapter proposes an auxiliary particle filter algorithm for inference in regime switching stochastic volatility models in which the regime state is governed by a first-order Markov chain. It proposes an ongoing updated Dirichlet distribution to estimate the transition probabilities of the Markov chain in the auxiliary particle filter. A simulation-based algorithm is presented for the method that demonstrates the ability to estimate a class of models in which the probability that the system state transits from one regime to a different regime is relatively high. The methodology is implemented in order to analyze a real-time series, namely, the foreign exchange rate between the Australian dollar and the South Korean won.

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7

Owen, Roger, et Eugenio Oñate. Particle-Based Methods : Fundamentals and Applications. Ingramcontent, 2013.

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8

Owen, Roger, et Eugenio Oñate. Particle-Based Methods : Fundamentals and Applications. Springer, 2011.

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9

(Editor), Piotr Bretikopf, et Antonio Huerta (Editor), dir. Meshfree & Particle Based Approaches in Computational Mechanics. ISTE Publishing Company, 2004.

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10

Allen, Michael P., et Dominic J. Tildesley. Long-range forces. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198803195.003.0006.

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A wide variety of special techniques for handling long-range forces are explained in this chapter. This includes the traditional Ewald sum, and the particle-mesh methods that use a discrete Fourier transform. A number of techniques based on spherical truncation such as the Wolf method, the isotropic periodic sum and the reaction field are also considered. Techniques for larger systems such as the fast-multipole method, the multilevel summation approach, and the direct solution of Maxwell’s equations, are explained. The advantages and disadvantages of the different approaches are reviewed, and a number of methods for tackling long-range forces in inhomogeneous systems, particularly in a slab geometry, are presented.

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11

Wigmans, Richard. New Calorimeter Techniques. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198786351.003.0008.

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This chapter is dedicated to calorimeter techniques that have been developed since the first edition of this monograph was published (2000). The Dual Readout Method (DREAM) aims to combine the advantages of compensation (linearity, excellent hadron resolution, Gaussian line shape) with a certain amount of design flexibility. This method, based on simultaneous detection of scintillation and Cherenkov light produyced in the shower development, eliminates some of the disadvantages of compensating devices, and in particular the dependence on efficient neutron detection of the latter. The Particle Flow Analysis method aims to combine the information provided by a good tracking system with that provided by a fine-grained calorimeter system to obtain excellent performance for the detection of jets. The results achieved with both methods, and the challenges faced in practice, are described in detail.

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12

Comesaña, Daniel Fernández. Scan-based sound visualisation methods using sound pressure and particle velocity. 2014.

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13

Single Molecule Tools, Part B:Super-Resolution, Particle Tracking, Multiparameter, and Force Based Methods. Elsevier, 2010. http://dx.doi.org/10.1016/c2009-0-62452-1.

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14

Horing, Norman J. Morgenstern. Quantum Mechanical Ensemble Averages and Statistical Thermodynamics. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198791942.003.0006.

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Chapter 6 introduces quantum-mechanical ensemble theory by proving the asymptotic equivalence of the quantum-mechanical, microcanonical ensemble average with the quantum grand canonical ensemble average for many-particle systems, based on the method of Darwin and Fowler. The procedures involved identify the grand partition function, entropy and other statistical thermodynamic variables, including the grand potential, Helmholtz free energy, thermodynamic potential, Gibbs free energy, Enthalpy and their relations in accordance with the fundamental laws of thermodynamics. Accompanying saddle-point integrations define temperature (inverse thermal energy) and chemical potential (Fermi energy). The concomitant emergence of quantum statistical mechanics and Bose–Einstein and Fermi–Dirac distribution functions are discussed in detail (including Bose condensation). The magnetic moment is derived from the Helmholtz free energy and is expressed in terms of a one-particle retarded Green’s function with an imaginary time argument related to inverse thermal energy. This is employed in a discussion of diamagnetism and the de Haas-van Alphen effect.

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15

Deruelle, Nathalie, et Jean-Philippe Uzan. The wave vector of light. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198786399.003.0022.

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This chapter shows how simple world lines of zero length can describe an undulatory aspect of light—namely, its frequency. It first encodes the information about the frequency of a monochromatic light wave in the zeroth component of its wave vector. An alternative method of taking into account the wave nature of light is based on the fact that the emission of successive light corpuscles by the source also defines the period of a light signal. To illustrate, the chapter provides the example of a light source and a receiver moving along the X axis of a frame S. Finally, this chapter illustrates the idea of a particle horizon as well as the limits of validity of the spectral shift formulas introduced in the chapter by the example of two objects which exchange light signals.

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16

Campbell, John, Joey Huston et Frank Krauss. QCD at Fixed Order : Technology. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199652747.003.0003.

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This chapter is devoted to the technology of fixed-order calculations, in particular, in QCD. After a short summary of methods for the efficient evaluation of tree-level scattering amplitudes for multi-particle production, and their integration in phase space, next-to leading order corrections in QCD are addressed. Techniques for the evaluation of loop amplitudes with modern methods, based on the reduction to master integrals, either analytically or with numerical unitarity cut methods, are discussed in some detail. After identifying the problem of infrared divergences and illuminating their treatment with a toy model, Catani-Seymour subtraction is explicitly introduced and exemplified for two cases, namely inclusive hadron production in electron-positron annihilation and inclusive W boson production in hadron collisions. This chapter concludes with some remarks concerning the rapidly developing field of next-to-next-to leading order calculations.

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17

Quintana, José Mario, Carlos Carvalho, James Scott et Thomas Costigliola. Extracting S&P500 and NASDAQ Volatility : The Credit Crisis of 2007–2008. Sous la direction de Anthony O'Hagan et Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.13.

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This article demonstrates the utility of Bayesian modelling and inference in financial market volatility analysis, using the 2007-2008 credit crisis as a case study. It first describes the applied problem and goal of the Bayesian analysis before introducing the sequential estimation models. It then discusses the simulation-based methodology for inference, including Markov chain Monte Carlo (MCMC) and particle filtering methods for filtering and parameter learning. In the study, Bayesian sequential model choice techniques are used to estimate volatility and volatility dynamics for daily data for the year 2007 for three market indices: the Standard and Poor’s S&P500, the NASDAQ NDX100 and the financial equity index called XLF. Three models of financial time series are estimated: a model with stochastic volatility, a model with stochastic volatility that also incorporates jumps in volatility, and a Garch model.

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18

Martínez-Pérez, M. J., R. Kleiner et D. Koelle. NanoSQUIDs Applied to the Investigation of Small Magnetic Systems. Sous la direction de A. V. Narlikar. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780198738169.013.19.

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This article discusses the use of nanoSQUIDs for investigating small magnetic systems. It begins with an overview of the basics of superconducting quantum interference devices, focusing on how a dc SQUID operates and the use of resistively and capacitively shunted junction model to describe the phase dynamics of Josephson junctions (JJs). It then considers the motivation for using nanoSQUIDs, along with the importance of their size and geometry. It also evaluates micro- and nanoSQUIDs made of various types of JJs including nanoSQUIDs based on sandwich-like junctions, constriction-like junctions, and proximized structures. After reviewing different nanoSQUID readout methods that can be used to directly sense the stray magnetic field created by a nanoscale magnetic sample, the article concludes by highlighting some of the practical constraints and challenges encountered in using nanoSQUID technology, including particle positioning with respect to the sensor’s surface.

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