Computational Physics
Problem Solving with Python
4th Edition
Published on 17. April 2024
Book
Paperback/Softback
592 pages
978-3-527-41425-3 (ISBN)
Description
Fourth edition of a classic on computational physics with new chapters on data science, machine learning and general relativity, plus a plethora of supplementary materials.
More details
Edition
4. Auflage
Language
English
Place of publication
Berlin
Germany
Target group
College/higher education
Illustrations
300
300 s/w Abbildungen
300 schwarz-weiße Abbildungen
Dimensions
Height: 244 mm
Width: 172 mm
Thickness: 33 mm
Weight
1120 gr
ISBN-13
978-3-527-41425-3 (9783527414253)
Schweitzer Classification
Other editions
Additional editions
Rubin H. Landau | Manuel J. Páez | Cristian C. Bordeianu
Computational Physics
Problem Solving with Python
E-Book
03/2024
4th Edition
Wiley-VCH
€102.99
Available for download
Rubin H. Landau | Manuel J. Páez | Cristian C. Bordeianu
Computational Physics
Problem Solving with Python
E-Book
03/2024
4th Edition
Wiley-VCH
€102.99
Available for download
Previous edition
Rubin H. Landau | Manuel J. Páez | Cristian C. Bordeianu
Computational Physics
Problem Solving with Python
Book
07/2015
3rd Edition
Wiley-VCH
€109.00
Article exhausted; check for reprint
Persons
Rubin H. Landau is Professor Emeritus in the Department of Physics at Oregon State University in Corvallis. He has been teaching courses in computational physics for over 25 years, was a founder of the Computational Physics Degree Program and the Northwest Alliance for Computational Science and Engineering, and has been using computers in theoretical physics research ever since graduate school. He is author of more than 90 refereed publications and has also authored books on Quantum Mechanics, Workstations and Supercomputers, the first two editions of Computational Physics, and a First Course in Scientific Computing.
Manuel J. Páez is a professor in the Department of Physics at the University of Antioquia in Medellín, Colombia. He has been teaching courses in Modern Physics, Nuclear Physics, Computational Physics, Mathematical Physics as well as programming in Fortran, Pascal and C languages. He and Professor Landau have conducted pioneering computational investigations in the interactions of mesons and nucleons with nuclei.
Cristian C. Bordeianu taught Physics and Computer Science at the Military College "Stefan cel Mare" in Câmpulung Moldovenesc, Romania.
Manuel J. Páez is a professor in the Department of Physics at the University of Antioquia in Medellín, Colombia. He has been teaching courses in Modern Physics, Nuclear Physics, Computational Physics, Mathematical Physics as well as programming in Fortran, Pascal and C languages. He and Professor Landau have conducted pioneering computational investigations in the interactions of mesons and nucleons with nuclei.
Cristian C. Bordeianu taught Physics and Computer Science at the Military College "Stefan cel Mare" in Câmpulung Moldovenesc, Romania.
Content
Preface
PART I. BASICS
Introduction
Software Basics
Errors & Uncertainties
Monte Carlo Simulations
Differentiation & Integration
Trial-and-Error Searching & Data Fitting
Matrix Computing and N-D Searching
Differential Equations & Nonlinear Oscillations
PART II. DATA SCIENCE
Fourier Analyses
Wavelet & Principal Components Analysis
Neural Networks & Machine Learning
Quantum Computing
PART III. APPLICATIONS
ODE Applications; Eigenvalues, Scattering, Trajectories
Fractals & Statistical Growth Models
Nonlinear Population Dynamics
Nonlinear Dynamics of Continuous Systems
Thermodynamics Simulations & Fenyman Path Integrals
Molecular Dynamics Simulations
General Relativity
Integral Equations
PART IV. PDE APPLICATIONS
PDE Review, Electrostatics & Relaxation
Heat Flow & Leapfrogging
String & Membrane Waves
Quantum Wave Packets & EM Waves
Shock & Soliton Waves
Fluid Hydrodynamics
Finite Element Electrostatics
Appendices
Index
PART I. BASICS
Introduction
Software Basics
Errors & Uncertainties
Monte Carlo Simulations
Differentiation & Integration
Trial-and-Error Searching & Data Fitting
Matrix Computing and N-D Searching
Differential Equations & Nonlinear Oscillations
PART II. DATA SCIENCE
Fourier Analyses
Wavelet & Principal Components Analysis
Neural Networks & Machine Learning
Quantum Computing
PART III. APPLICATIONS
ODE Applications; Eigenvalues, Scattering, Trajectories
Fractals & Statistical Growth Models
Nonlinear Population Dynamics
Nonlinear Dynamics of Continuous Systems
Thermodynamics Simulations & Fenyman Path Integrals
Molecular Dynamics Simulations
General Relativity
Integral Equations
PART IV. PDE APPLICATIONS
PDE Review, Electrostatics & Relaxation
Heat Flow & Leapfrogging
String & Membrane Waves
Quantum Wave Packets & EM Waves
Shock & Soliton Waves
Fluid Hydrodynamics
Finite Element Electrostatics
Appendices
Index