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Computational Physics - An introductory course (Lecture Notes for an upper-division undergraduate computational physics course)

Computational Physics - An introductory course (Lecture Notes for an upper-division undergraduate computational physics course)

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Computational Physics - An introductory course (Lecture Notes for an upper-division undergraduate computational physics course)

Computational Physics - An introductory course (Lecture Notes for an upper-division undergraduate computational physics course) Summary:

 
  • A complete set of lecture notes for an upper-division undergraduate computational physics course. Topics covered include scientific programming in C, the numerical solution of ordinary and partial differential equations, particle-in-cell codes, and Montecarlo methods.
  • Introduction
    • Intended audience
    • Major sources
    • Purpose of course
    • Course philosophy
    • Programming methodologies
    • Scientific programming languages

  • Scientific programming in C
    • Introduction
    • Variables
    • Expressions and statements
    • Operators
    • Library functions
    • Data input and output
    • Structure of a C program
    • Control statements
    • Functions
    • Pointers
    • Global variables
    • Arrays
    • Character strings
    • Multi-file programs
    • Command line parameters
    • Timing
    • Random numbers
    • C++ extensions to C
    • Complex numbers
    • Variable size multi-dimensional arrays
    • The CAM graphics class

  • Integration of ODEs
    • Introduction
    • Euler's method
    • Numerical errors
    • Numerical instabilities
    • Runge-Kutta methods
    • An example fixed-step RK4 routine
    • An example calculation
    • Adaptive integration methods
    • An example adaptive-step RK4 routine
    • Advanced integration methods
    • The physics of baseball pitching
    • Air drag
    • The Magnus force
    • Simulations of baseball pitches
    • The knuckleball

  • The chaotic pendulum
    • Introduction
    • Analytic solution
    • Numerical solution
    • Validation of numerical solutions
    • The Poincaré section
    • Spatial symmetry breaking
    • Basins of attraction
    • Period-doubling bifurcations
    • The route to chaos
    • Sensitivity to initial conditions
    • The definition of chaos
    • Periodic windows
    • Further investigation

  • Poisson's equation
    • Introduction
    • 1-d problem with Dirichlet boundary conditions
    • An example tridiagonal matrix solving routine
    • 1-d problem with mixed boundary conditions
    • An example 1-d Poisson solving routine
    • An example solution of Poisson's equation in 1-d
    • 2-d problem with Dirichlet boundary conditions
    • 2-d problem with Neumann boundary conditions
    • The fast Fourier transform
    • An example 2-d Poisson solving routine
    • An example solution of Poisson's equation in 2-d
    • Example 2-d electrostatic calculation
    • 3-d problems

  • The diffusion equation
    • Introduction
    • 1-d problem with mixed boundary conditions
    • An example 1-d diffusion equation solver
    • An example 1-d solution of the diffusion equation
    • von Neumann stability analysis
    • The Crank-Nicholson scheme
    • An improved 1-d diffusion equation solver
    • An improved 1-d solution of the diffusion equation
    • 2-d problem with Dirichlet boundary conditions
    • 2-d problem with Neumann boundary conditions
    • An example 2-d diffusion equation solver
    • An example 2-d solution of the diffusion equation
    • 3-d problems

  • The wave equation
    • Introduction
    • The 1-d advection equation
    • The Lax scheme
    • The Crank-Nicholson scheme
    • Upwind differencing
    • The 1-d wave equation
    • The 2-d resonant cavity

  • Particle-in-cell codes
    • Introduction
    • Normalization scheme
    • Solution of electron equations of motion
    • Evaluation of electron number density
    • Solution of Poisson's equation
    • An example 1D PIC code
    • Results
    • Discussion

  • Monte-Carlo methods
    • Introduction
    • Random numbers
    • Distribution functions
    • Monte-Carlo integration
    • The Ising model
 
 
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Computational Physics - An introductory course (Lecture Notes for an upper-division undergraduate computational physics course) Keywords

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