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Titlebook: Computational Physics; Simulation of Classi Philipp O. J. Scherer Textbook 20101st edition Springer-Verlag Berlin Heidelberg 2010 Algorithm

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發(fā)表于 2025-3-21 17:37:32 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Computational Physics
副標題Simulation of Classi
編輯Philipp O. J. Scherer
視頻videohttp://file.papertrans.cn/233/232897/232897.mp4
概述Explains numerical techniques and provides many examples to which these can be applied.Teaches the basics of numerical methods.Explains the simulation of classical and quantum systems.Summarizes vario
圖書封面Titlebook: Computational Physics; Simulation of Classi Philipp O. J. Scherer Textbook 20101st edition Springer-Verlag Berlin Heidelberg 2010 Algorithm
描述This book encapsulates the coverage for a two-semester course in computational physics. The first part introduces the basic numerical methods while omitting mathematical proofs but demonstrating the algorithms by way of numerous computer experiments. The second part specializes in simulation of classical and quantum systems with instructive examples spanning many fields in physics, from a classical rotor to a quantum bit. All program examples are realized as Java applets ready to run in your browser and do not require any programming skills.
出版日期Textbook 20101st edition
關(guān)鍵詞Algorithms for computer experiments; Classical and quantum systems; Computer experiments; Interpolation
版次1
doihttps://doi.org/10.1007/978-3-642-13990-1
isbn_ebook978-3-642-13990-1
copyrightSpringer-Verlag Berlin Heidelberg 2010
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發(fā)表于 2025-3-21 23:18:27 | 只看該作者
https://doi.org/10.1007/978-3-7908-1954-0 the sampling frequency of audio or video signals, interpolation methods are necessary. But interpolation is also helpful to develop more sophisticated numerical methods for the calculation of numerical derivatives or integrals. Polynomial interpolation is discussed in large detail together with its
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https://doi.org/10.1007/978-3-7908-1954-0on with pivoting are sufficient which decompose the coefficient matrix into a product of a lower and an upper triangular matrix. An alternative method is QR decomposition which is numerically more stable in certain cases. Both these methods are compared in a computer experiment. Special and very eff
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https://doi.org/10.1007/978-3-7908-1954-0points can be found as the roots of the derivative. Elementary methods in one dimension are bisection, the regula falsi method, the Newton–Raphson, and secant methods. The efficiency of these methods is compared in a computer experiment. For functions of more than one variable the method of steepest
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Theory and Theoretical Framework,of thermodynamical averages Monte Carlo methods are very useful which sample the integration volume at randomly chosen points. This chapter begins with some basic statistics. Probability density and cumulative distribution are introduced. The construction of a histogram is described. The central lim
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https://doi.org/10.1007/978-1-4471-4591-2ymmetric, if real) matrix. The direct solution of the eigenvalue problem is only possible for matrices of very small dimension. For medium-sized problems the Jacobi method or reduction to tridiagonal form by a series of Householder reflections are appropriate. Special algorithms are available for ma
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Oksana Soshko,Yuri Merkuryev,Martins Chakstescribe a functional relationship between two or more variables by a smooth curve, i.e., to fit a certain model to the data. If uncertainties of the data are negligibly small, an exact fit is possible, for instance, with polynomials, spline functions, or trigonometric functions. If the uncertainties
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