Computational physics : problem solving with python / Rubin H. Landau, Manuel J. Páez and Cristian C. Bordeianu.

This edition originally published: 2004.

Includes bibliographical references and index.

Computing Software Basics -- Errors and Uncertainties in Computations -- Monte Carlo: Randomness, Walks, and Decays -- Differentiation and Integration -- Matrix Computing -- Trial-and-Error Searching and Data Fitting -- Solving Differential Equations: Nonlinear Oscillations -- ODE Applications: Eigenvalues, Scattering, and Projectiles -- High-Performance Hardware and Parallel Computers -- Applied HPC: Optimization, Tuning, and GPU Programming -- Fourier Analysis: Signals and Filters -- Wavelet and Principal Components Analyses: Nonstationary Signals and Data Compression -- Nonlinear Population Dynamics -- Continuous Nonlinear Dynamics -- Fractals and Statistical Growth Models -- Thermodynamic Simulations and Feynman Path Integrals -- Molecular Dynamics Simulations -- PDE Reviewand Electrostatics via Finite Differences and Electrostatics via Finite Differences -- Heat Flow via Time Stepping -- Wave Equations I: Strings and Membranes -- Wave Equations II: QuantumPackets and Electromagnetic -- Electrostatics via Finite Elements -- Shocks Waves and Solitons -- Dynamics -- Integral Equations of QuantumMechanics.

The use of computation and simulation has become an essential part of the scientific process. Being able to transform a theory into an algorithm requires significant theoretical insight, detailed physical and mathematical understanding, and a working level of competency in programming.