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Titlebook: Computational Physics; Simulation of Classi Philipp O.J. Scherer Textbook 2017Latest edition Springer Nature Switzerland AG 2017 Understand

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發(fā)表于 2025-3-21 16:52:30 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Computational Physics
副標(biāo)題Simulation of Classi
編輯Philipp O.J. Scherer
視頻videohttp://file.papertrans.cn/233/232895/232895.mp4
概述Teaches basic numerical methods in theoretical physics.Features numerous computer examples, for which no programming skills are required.Provides detailed explanations without mathematical proofs.Disc
叢書(shū)名稱Graduate Texts in Physics
圖書(shū)封面Titlebook: Computational Physics; Simulation of Classi Philipp O.J. Scherer Textbook 2017Latest edition Springer Nature Switzerland AG 2017 Understand
描述This textbook presents basic numerical methods and applies them to a large variety of physical models in multiple computer experiments. Classical algorithms and more recent methods are explained. Partial differential equations are treated generally comparing important methods, and equations of motion are solved by a large number of simple as well as more sophisticated methods. Several modern algorithms for quantum wavepacket motion are compared. The first part of the book discusses the basic numerical methods, while the second part simulates classical and quantum systems. Simple but non-trivial examples from a broad range of physical topics offer readers insights into the numerical treatment but also the simulated problems. Rotational motion is studied in detail, as are simple quantum systems. A two-level system in an external field demonstrates elementary principles from quantum optics and simulation of a quantum bit. Principles of molecular dynamics are shown. Modern boundary elementmethods are presented in addition to standard methods, and waves and diffusion processes are simulated comparing the stability and efficiency of different methods. A large number of computer experimen
出版日期Textbook 2017Latest edition
關(guān)鍵詞Understanding Computer Simulation; Inhomogeneous Linear Equations; Simulation of Classical and Quantum
版次3
doihttps://doi.org/10.1007/978-3-319-61088-7
isbn_softcover978-3-319-87002-1
isbn_ebook978-3-319-61088-7Series ISSN 1868-4513 Series E-ISSN 1868-4521
issn_series 1868-4513
copyrightSpringer Nature Switzerland AG 2017
The information of publication is updating

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978-3-319-87002-1Springer Nature Switzerland AG 2017
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Wieland Appelfeller,Wolfgang Buchholznction are roots of the gradient. In one dimension bisection is a very robust but rather inefficient root finding method. If a good starting point close to the root is available and the function smooth enough, the Newton–Raphson method converges much faster. Special strategies are necessary to find
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,IT-Unterstützung in der Beschaffung,tion of convolution integrals. In this chapter we discuss the discrete Fourier transformation as a numerical approximation to the continuous Fourier integral. It can be realized efficiently by Goertzel’s algorithm or the family of fast Fourier transformation methods. Computer experiments demonstrate
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Zusammenfassende Betrachtung und Ausblick, of thermodynamic averages e.g., Monte Carlo methods are very useful which sample the integration volume at randomly chosen points. In this chapter we discuss algorithms for the generation of pseudo-random numbers with given probability distribution which are essential for all Monte Carlo methods. W
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