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

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Zusammenfassende Betrachtung und Ausblick,e show how the efficiency of Monte Carlo integration can be improved by sampling preferentially the important configurations. Finally the famous Metropolis algorithm is applied to classical many-particle systems and nonlinear optimization problems.

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Supplier Relationship Managementnserve the orthogonality of the rotation matrix. Omelyan’s implicit quaternion method is very efficient and conserves orthogonality exactly. In computer experiments we compare different explicit and implicit methods for a free rotor, we simulate a rotor in an external field and the collision of two rotating molecules.

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Thermodynamic Systemsplied to a one- or two-dimensional system of interacting spins (Ising model). The thermodynamic average is taken over a set of random configurations. We study the average magnetization in a magnetic field and the phase transition to the ferromagnetic state.

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Random Numbers and Monte-Carlo Methodse show how the efficiency of Monte Carlo integration can be improved by sampling preferentially the important configurations. Finally the famous Metropolis algorithm is applied to classical many-particle systems and nonlinear optimization problems.

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1868-4513 vides detailed explanations without mathematical proofs.DiscThis 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 g

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,IT-Unterstützung in der Beschaffung,ntegral. It can be realized efficiently by Goertzel’s algorithm or the family of fast Fourier transformation methods. Computer experiments demonstrate trigonometric interpolation and nonlinear filtering as applications.

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