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% *======================================================================*
%  Cactus Thorn template for ThornGuide documentation
%  Author: Ian Kelley
%  Date: Sun Jun 02, 2002
%  $Header: /cactusdevcvs/Cactus/doc/ThornGuide/template.tex,v 1.12 2004/01/07 20:12:39 rideout Exp $
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% If you are using CVS use this line to give version information
% $Header: /cactusdevcvs/Cactus/doc/ThornGuide/template.tex,v 1.12 2004/01/07 20:12:39 rideout Exp $

\documentclass{article}

% Use the Cactus ThornGuide style file
% (Automatically used from Cactus distribution, if you have a
%  thorn without the Cactus Flesh download this from the Cactus
%  homepage at www.cactuscode.org)
\usepackage{../../../../doc/latex/cactus}

\begin{document}

% The author of the documentation
\author{Ian Hawke \textless hawke@aei.mpg.de\textgreater}

% The title of the document (not necessarily the name of the Thorn)
\title{Adaptive Mesh Refinement}

% the date your document was last changed, if your document is in CVS,
% please use:
%    \date{$ $Date: 2004/01/07 20:12:39 $ $}
\date{November 05 2004}

\maketitle

% Do not delete next line
% START CACTUS THORNGUIDE

% Add all definitions used in this documentation here
%   \def\mydef etc

% Add an abstract for this thorn's documentation
\begin{abstract}
  A brief description of how to use AMR.
\end{abstract}

% The following sections are suggestive only.
% Remove them or add your own.

\section{Introduction}

This thorn is a regridding thorn to work with {\tt Carpet}. It is
meant to directly replace the standard {\tt CarpetRegrid} thorn and
many of the parameters are based directly on standard parameters that
people already use. However, this thorn is meant to provide full {\em
  Adaptive} Mesh Refinement (AMR). The thorn is not complete by
itself; as described below, an error indicator needs to be given.

As those that use mesh refinement will know, the question of where to
put the refined grids is as much art as science. The crucial points
are the following:
\begin{enumerate}
\item We wish to refine as few points as possible. The reason for this
  is to reduce memory overhead and to reduce runtime. The latter is
  particularly important as the runtime is essentially dominated by
  the finest level(s).
\item We wish to create as few new grids as possible. The reason for
  this is that the ghost zones required for the boundaries of the
  grids are, in a sense, a waste of computational time. Therefore the
  larger the boundaries the more time the code will spend filling
  zones that have no benefit for the evolution. The more grids, the
  larger the boundary for any given benefit.
\item We wish to place the refined grid(s) where they will do the most
  good; that is, where the error is highest. This allows us to get a
  (more) uniform error over the whole domain.
\end{enumerate}
Therefore the problem to be solved is to balance requirements (1) and
(2) in a sensible way whilst ensuring that the error is minimized as
required by point (3).

The process by which this is achieved is twofold:
\begin{enumerate}
\item An approximation to the error is found. For ``true'' AMR this is
  usually meant to be an approximation to the truncation error found
  using Richardson extrapolation and a shadow heirachy. However, this
  can be expensive and may not work well at low resolutions
  (particularly in the {\tt Carpet} case when a large number of buffer
  zones are in use). Instead a separate approximation can be used
  (often called an {\em error indicator} instead of a true {\em error
    estimate}) based on certain physical properties of the solution,
  such as a curvature based method (such as is used in {\tt Paramesh}).
\item The points marked in error are then ``clustered'' into Cartesian
  boxes. The Cartesian boxes can either be pre-determined (as in {\tt
    Paramesh}) or computed on-the-fly, as done here. It might be that
  a box is refined only if a certain fraction of its points are marked
  in error (I believe this is the {\tt Paramesh} approach) or that
  every point marked in error is contained in a refined box, which is
  the approach taken here.
\end{enumerate}
Essentially, this thorn requires somebody else to compute the
approximation to the error and to store it in a grid function. It will
then cluster the points in error, providing {\tt Carpet} with a new
grid structure.

For those that want the real details, this is basically an
implementation of the clustering algorithm of Berger and
Rigoutsos~\cite{CAR_Berger91}.

\section{Using This Thorn}

As a user you should just replace {\tt CarpetRegrid} with {\tt
  CarpetAdaptiveRegrid} in your parameter file and set the appropriate
parameters correctly:
\begin{itemize}
\item {\tt Carpet::domain\_from\_coordbase}. This {\bf must} be set to
  {\tt "yes"}. It follows that you must set your domain using the
  coordbase parameters. Some examples can be found in the {\tt par/}
  directory of this thorn.
\item {\tt min\_width}. This describes the minimum width of a grid in
  any direction. Note that if the entire {\em global} domain is
  smaller than this in a given direction then it will be ignored for
  that direction (local domain sizes will be treated in the correct,
  processor independent manner). The value of this should be set
  dependent on the number of Carpet {\tt ghost\_zone}s and {\tt
    buffer\_zone}s you are using; for example, with 3 {\tt
    ghost\_zone}s and 6 {\tt buffer\_zone}s I would set this to be at
  least 20 ($> 2 \times (3+6)$).
\item {\tt min\_fraction}. This describes the minimum fraction of
  points marked in error that a candidate refined box should have
  before it is accepted. Note that this may be ignored if the result
  would be to produce a box that is too small. This should not be set
  too high or the algorithm will produce large numbers of small boxes;
  I would recommend a value between 0.5 and 0.8.
\item {\tt max\_error}. If the absolute value of the grid function
  being used as an approximation to the error is above this the point
  is marked in error; if not, the point is marked as fine. Sensible
  values depend entirely on the method used to compute the error
  approximation and you'll almost certainly need to experiment.
\item {\tt error\_var}. The name of the grid function containing the
  approximation to the error. Should have the form {\tt
    Thorn::Var}. Should be a real grid function with storage, probably
  with only one timelevel, and almost certainly should have the tags
  table entry {\tt tags='Prolongation="None"'} (otherwise the error
  function will be the same on different refinement levels, which is
  not what you want).
\item {\tt regrid\_every}. How often the regridding algorithm is
  called; semantically it's identical to the parameter in {\tt
    CarpetRegrid}. Again, the value of this parameter probably
  requires some experimentation. Note, however, that successively
  refining a region many times at short notice often does not give
  good results, as it is similar to repeatedly interpolating the grid
  functions in that region.
\item {\tt pad}. When the error is computed and points are marked in
  error or not, the result is ``padded'' by a certain number of
  points. This ensures that it doesn't try to regrid a single point -
  this will always be padded out to something larger. It also ensures
  that if the computation of the error estimate was non-local (i.e.,
  required taking derivatives) then inter-processor boundaries don't
  cause problems. It also ensures that if a feature is near the
  threshold of being refined the error doesn't have ``gaps'' where
  points fall just below the threshold. Finally, it ensures that the
  refined grid is big enough to allow the interesting feature to move
  within it. The value for this should be set with these
  considerations in mind; typically I would choose 4-8 points but if
  {\tt regrid\_every} is large, or the features are moving rapidly on
  the grid, or you have a large number of {\tt ghost\_zone}s, then you
  may wish to increase it to 12 or more.
\item {\tt verbose} and {\tt veryverbose}. Prints large amounts of
  debugging information about the grid locations. I wouldn't use these
  unless you want to debug.
\item {\tt refinement\_levels}. The number of refinement levels to be
  set up initially, including the base grid. Again this follows the
  semantics of {\tt CarpetRegrid}. At the initial time the grid
  structure is determined not from the error function (as it may not
  have been computed as yet) but instead from this parameter and the
  {\tt coordinates} parameter:
\item {\tt coordinates}. The bounding box coordinates for the initial
  grid structure. Again this follows precisely the semantics of {\tt
    CarpetRegrid} {\bf with the assumption equivalent to}

 {\tt CarpetRegrid::smart\_outer\_boundaries = "yes"}.
 
 As noted above it can be very bad for a large number of refined grids
 to be switched on very rapidly, so judicious use of this parameter to
 set up the initial grid structure can be very helpful.
\end{itemize}

{\tt CarpetAdaptiveRegrid} should give identical results on varying
numbers of processors.

{\tt CarpetAdaptiveRegrid} will be default produce as many refinement
levels as allowed by the

 {\tt Carpet::max\_refinement\_levels}
 
 parameter, so be careful!

{\tt CarpetAdaptiveRegrid} will {\bf not} necessarily give a
symmetrical grid structure on symmetrical problems. This may mean that
any symmetry in the problem that is not explicitly imposed (say by the
boundary conditions) could be lost when using this thorn. This is a
feature, not a bug. If you don't like it, you're welcome to try and
fix it.

{\tt CarpetAdaptiveRegrid} is in the development directory of the
development version of {\tt Carpet} for good reason; use at your own
risk.

\begin{thebibliography}{9}

\bibitem{CAR_Berger91}
{M. Berger and I. Rigoutsos. 
\newblock An {A}lgorithm for {P}oint {C}lustering and {G}rid
{G}eneration. 
\newblock {\em IEEE Trans. on Systems, Man.\ and Cybernetics}, {\bf
  21}:\penalty0 1278--1286, 1991.}

\end{thebibliography}

% Do not delete next line
% END CACTUS THORNGUIDE

\end{document}