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[lectures/latex.git] / computational_physics / cp.tex

\documentclass[pdf]{prosper}

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\title{introduction to computational physics}
\subtitle{basic concepts and approaches}
\author{frank zirkelbach}
\email{frank.zirkelbach@physik.uni-augsburg.de}
\institution{experimantal physics {\footnotesize IV} - university of augsburg}

\begin{document}

\maketitle

\overlays{5}{
\begin{slide}{outline}
\begin{itemstep}
  \item motivation
  \item history of computing hardware/software
  \item warning
  \item computational techniques
  \item summary
\end{itemstep}
\end{slide}}

\overlays{4}{
\begin{slide}{motivation}
\FromSlide{1}{
  \begin{center}
  \begin{figure}[h]
  \includegraphics[width=8cm]{cp_appl_field.eps}
  \end{figure}
  \end{center}
}
\FromSlide{2}{
challenge:
}
\FromSlide{3}{
\begin{itemize}
  \item precise mathematical theory
  \item often: solving theory's equations ab-initio is not realistic
  \item only a few models can be solved exactly
\end{itemize}}
\FromSlide{4}{
$\Rightarrow$ study and implementation of numerical algorithms
}
\end{slide}}

\overlays{5}{
\begin{slide}{history of computing hardware}
  \begin{minipage}[t]{10cm}
     \onlySlide*{1}{\begin{center} \includegraphics[height=3cm]{abacus.eps} \end{center}}
     \onlySlide*{2}{\begin{center} \includegraphics[height=3cm]{eniac.eps} \hspace{1cm} \includegraphics[height=3cm]{tube.eps} \end{center}}
     \onlySlide*{3}{\begin{center} \includegraphics[height=3cm]{z1.eps} \end{center}}
     \onlySlide*{4}{\begin{center} \includegraphics[height=3cm]{pdp1.eps} \hspace{1pt} \includegraphics[height=3cm]{transistor.eps} \end{center}}
     \onlySlide*{5}{\begin{center} \includegraphics[height=3cm]{pdp8.eps} \hspace{1cm} \includegraphics[height=3cm]{ic.eps} \end{center}}
     %\FromSlide{6}{\begin{center} \includegraphics[height=3cm]{} \end{center}}
  \end{minipage}
  \begin{minipage}[b]{10cm}
    \begin{itemstep}
      \item $3000 \, bc$: abacus - first calculating device
      \item $1945$: eniac - electrical digital computer
      \item $1938/41$: z1/3 - featuring memory and programmability
      \item $1960$: pdp-1 - transistor based computers
      \item $1964$: pdp-8 - integrated circuit computers
    \end{itemstep}
  \end{minipage}
\end{slide}}

\overlays{6}{
\begin{slide}{history of computing hardware}
  \begin{minipage}[t]{10cm}
     \onlySlide*{1}{\begin{center} \includegraphics[height=3cm]{4004.eps} \end{center}}
     \onlySlide*{2}{\begin{center} \includegraphics[height=3cm]{cray2.eps} \hspace{1pt} \includegraphics[height=3cm]{cray2_i.eps} \end{center}}
     \onlySlide*{3}{\begin{center} \includegraphics[height=3cm]{apple2.eps} \includegraphics[height=3cm]{c64.eps} \end{center}}
     \onlySlide*{4}{\begin{center} \includegraphics[height=3cm]{intel1.eps} \includegraphics[height=3cm]{intel2.eps} \end{center}}
     \onlySlide*{5}{\begin{center} \includegraphics[height=3cm]{mips.eps} \hspace{1pt} \includegraphics[height=3cm]{ppc.eps} \end{center}}
     \onlySlide*{6}{\begin{center} \includegraphics[height=3cm]{cluster1.eps} \hspace{1cm} \includegraphics[height=3cm]{cluster2.eps} \end{center}}
  \end{minipage}
  \begin{minipage}[b]{10cm}
    \begin{itemstep}
      \item $1970$: intel 4004 - first single chip $\mu$-processor
      \item $1977/85$: cray1/2 - vector supercomputer
      \item $1977/82/85$: 6502/6510/m68k - first pc
      \item $1978/82/85 $: 8086/80286/80386
      \item $1985$: mips - first risc design
      \item $1990/2000$: massive parallel computing
    \end{itemstep}
  \end{minipage}
\end{slide}}

\overlays{11}{
\begin{slide}{history of computing software}
  \begin{itemstep}
    \item $1946$: plankalk"ul - high-level programming language
    \item $1950$: assembler - translating instruction mnemonics
    \item $1954$: fortran - {\scriptsize formula translation}
    \item $1963$: basic - {\scriptsize beginner's all purpose symbolic instruction code}
    \item $1964$: os/360 - batch processing operating system
    \item $1969$: unix - multics port to pdp-8, pdp-11/20
    \item $1972$: c programming language - thompson, ritchie
    \item $1978/84/85$: apple os/atari, amiga os/mac os
    \item $1981/85/92/95$: ms-dos/windows 1.0/3.x/95
    \item $1983$: gnu project - unix-like free software development
    \item $1991$: linux - open-source kernel
  \end{itemstep}
\end{slide}}

\overlays{4}{
\begin{slide}{warning - machine accuracy $\epsilon_m$}
  \begin{itemstep}
    \item numerical precision of 64-bit floating point \\
          ieee floating point format: $v = -1^s 2^{-e} m$ 
          \[
          \begin{array}{lll}
          s: & \textrm{signe} & \textrm{1 bit} \\
          m: & \textrm{mantissa} & \textrm{52 bit} \\
          e: & \textrm{exponent} & \textrm{11 bit} \\
          \end{array}
          \]
    \item $\epsilon_m$: smallest floating point with $1 + \epsilon_m \neq 1$ \\
          $\epsilon_m \approx 2 \times 10^{-18}$ \hspace{2pt} (roundoff error)
    \item $N$ arithmetic operations $\Rightarrow$ error of order $N \epsilon_m$
    \item subtraction of very nearly equal numbers\\
          (difference in few significant low-order bits)
  \end{itemstep}
\end{slide}}

\overlays{6}{
\begin{slide}{warning - truncation error}
  \begin{itemstep}
    \item discrete approximation of continuous quantity
    \item truncation error $\equiv$ discrepancy between true answer and practical calculation
    \item persists even on hypothetical perfect computer ($\epsilon_m = 0$)
    \item machine independent, characteristic of used algorithm
    \item numerical analysis: minimizing truncation error
    \item unstable method: roundoff error interacting at early stage
  \end{itemstep}
\end{slide}}

\overlays{4}{
\begin{slide}{warning - recursive functions}
  \begin{itemstep}
    \item avoid recursive functions!
          \verbatiminput{fak1.c}
    \item better:
          \verbatiminput{fak2.c}
  \end{itemstep}
\end{slide}}

\begin{slide}{computational techniques}
techniques discussed in the talk:
\begin{itemize}
  \item rough discretization
  \item solution of linear algebraic equations
  \item interpolation and extrapolation
  \item integration of functions
  %\item evaluation of (special) functions
  \item monte carlo methods
  \item eigensystems
  \item spectral applications
  %\item modeling of data
  %\item ordinary differential equations
  %\item two point boundary value problems
  %\item partial differential equations
\end{itemize}
\end{slide}

\begin{slide}{computational techniques}
techniques \textcolor{red}{not yet} discussed in the talk:\footnote{if time is available this will be completed. updates at:\\http://www.physik.uni-augsburg.de/\~{}zirkelfr/download/cp/cp.pdf\\read more at: http://www.nr.com}
\begin{itemize}
  %\item rough discretization
  %\item solution of linear algebraic equations
  %\item interpolation and extrapolation
  %\item integration of functions
  \item evaluation of (special) functions
  %\item monte carlo methods
  %\item eigensystems
  %\item spectral applications
  \item modeling of data
  \item ordinary differential equations
  \item two point boundary value problems
  \item partial differential equations
\end{itemize}
\hspace{6cm}
\end{slide}

\overlays{2}{
\begin{slide}{rough discretization}
  \begin{itemstep}
    \item example: homogenous field of force $\vec{F} = (0,-mg)$ \\
          \begin{tabular}{ll}
          equation of motion: & $\vec{F} = m \vec{a} = m \frac{d^2 \vec{r}}{dt^2}$ \\
          initial condition: & $\vec{r}(t=0) = \vec{r_0} = (x_0,y_0)$ \\
                             & $\frac{d \vec{r}}{dt}|_{t=0} = (v_{x_0},v_{y_0})$ \\
          \end{tabular}
    \item algorithm using discretized time ($T_{total} = N \tau$):
          \begin{tabular}{lll}
          $x^1 = x_0;$ & $y^1 = y_0;$ & \\
          $v^1_x = v_{x_0};$ & $v^1_y = v_{y_0};$ & \\
          loop: & $x^2 = x^1 + \tau v^1_x;$ & $y^2 = y^1 + \tau v^1_y;$ \\
                & $v^2_x = v^1_x;$ & $v^2_y = v^1_y + (-mg) \tau;$ \\
                & $x^1 = x^2;$ & $y^1 = y^2$ \\
                & $v^1_x = v^2_x;$ & $v^1_y = v^2_y;$ \\
          \end{tabular}
  \end{itemstep}
\end{slide}}

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\end{document}