Carpet — Adaptive Mesh Refinement for the Cactus Framework

Carpet logo (a Sierpiński carpet)

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Introduction (PDF, 170 kB)
First Steps (PDF, 90 kB)
Scheduling (PDF, 160 kB)
Grid Structure (PDF, 120 kB)
Internals (PDF, 130 kB)
Other Carpets

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AEI Potsdam
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Carpet is an adaptive mesh refinement and multi-patch driver for the Cactus Framework. Cactus is a software framework for solving time-dependent partial differential equations on block-structured grids, and Carpet acts as driver layer providing adaptive mesh refinement, multi-patch capability, as well as parallelisation and efficient I/O.

Carpet was created in 2001 by Erik Schnetter at the TAT (Theoretische Astrophysik Tübingen) and subsequently brought into production use by Erik Schnetter, Scott Hawley, and Ian Hawke at the AEI (Max-Planck-Institut für Gravitationsphysik, Albert-Einstein-Institut). Carpet is currently maintained at the CCT (Center for Computation & Technology) at LSU. These pages describe Carpet and its current development.


February 15, 2011: The download instructions for Carpet now also point to Google Code, where the current development version is availble for download.

November 23, 2010: We are pleased to announce the second release (code name "Chandrasekhar") of the Einstein Toolkit, an open, community developed software infrastructure for relativistic astrophysics. This release is mainly a maintenance release incorporating fixes accumulated since the previous release in June 2010, as well as additional test suites.

August 30, 2010: Notes from our Carpet Developer Workshop at RIT are now available.

June 17, 2010: We are pleased to announce the first release (code name "Bohr") of the Einstein Toolkit, an open, community developed software infrastructure for relativistic astrophysics. The Einstein Toolkit is a collection of over 130 software components and tools for simulating and analyzing general relativistic astrophysical systems that builds on numerous software efforts in the numerical relativity community including CactusEinstein, the Whisky hydrodynamics code, and the Carpet AMR infrastructure.

Old News...


We have accumulated a few pieces of documentation:

  • An introduction (PDF, 210 kB) to Carpet, as well as a guide to the first steps for using it. Everybody should have read this. (This is the same as the Arrangement Guide from the Carpet sources.)
  • Ulrich Sperhake wrote a tutorial outlining the first steps (PDF, 130 kB) that one has to take to install Carpet and run an example application.
  • An explanation of the internal workings (PDF, 120 kB) of Carpet. You should read this if you want to modify Carpet.
  • An explanation of how scheduling works (PDF, 120 kB) in (PUGH and) Carpet. This may be useful for setting up mixtures of local and global operations.
  • The individual Thorn Guides of Carpet. They are available with the source code. They give details about the thorns' APIs and user interfaces.
  • Thanks to Doxygen, we now have an overview over all the routines and data structures in Carpet. Most individual Doxygen tags are still missing, but the extracted documentation is already very useful. (The online documentation might not always be up to date; in case of doubt, extract the documentation yourself.)

Interacting with the developers

Most discussions about Carpet, i.e. user questions, feature requests, and bug reports, are held on the Cactus developers' mailing list You can subscribe and unsubscribe from our list management web page. You will also find the mailing list archive there.

We use TRAC to keep track of requested features or reported bugs in Carpet. You can submit or comment on issues from our TRAC site.

Pretty pictures

Here are some pretty pictures of simulations that were performed with Carpet:

lapse height field

Cut through a binary black hole system. Height field of the lapse function (approximately the time dilatation) in a binary black hole system calculated from Meudon initial data. The system is cut between the two black holes, so that only one black hole is visible. The white boxes indicate the hierarchy of refinement regions.

quadrupole wave

A quadrupole wave. Two rotating scalar charges create a quadrupolar wave, mimicking the gravitational wave trail of a binary black hole system. The small bumps and riddles are artifacts caused by the discontinuous charge distribution. To be improved.

lapse isosurfaces

Lapse isosurfaces in a binary black hole system. The same system as above, but the lapse function is rendered as isosurfaces.

velocity component

A velocity component in a stellar core collapse. The x component of the fluid velocity in a stellar core collapse. This simulation was performed by Christian Ott.

error function

The error in a multipatch numerical simulation of scalar wave propagation in a hollow spherical shell. The coarse- and fine-grid surface show the numerical errors (computed solution - exact solution) computed at two different resolutions, with the low resolution error divided by 16. The fact that the two surfaces overlap nicely shows that the errors scale as the 4th power of the grid resolution. This simulation was performed by Jonathan Thornburg.

matter density

The fate of a proto-neutron-star bar-mode deformation. Matter density at z=0 during the transition from an m=2 deformed star to an m=1 deformed one. The light on the right is used to emphasizes the spiral arms which are responsible for a small mass loss. This simulation was performed by Gian Mario Manca.

Moving pictures: We can show a movie (animated gif, 3.3 MB) of a scalar wave equation with adaptive mesh refinement. The refinement criterion is a very simplistic local truncation error estimate. We also have a movie (animated gif, 730 kB) of a moving refinement region tracking a black hole.

Making sense of results

Three-dimensional time-dependent simulation results are difficult enough to interpret when the grid is uniform. With mesh refinement, the sheer amount of available data makes it necessary to use professional tools to examine the data. This is not only the case for "big physics runs", where one (should) know in advance what to expect, but especially during development, where things do not always go as planned. Christian Reisswig was kind enough to write a database plugin for the visualisation tool VisIt. There is also an import module for the visualisation tool OpenDX available, implemented by Thomas Radke.

Related projects

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Erik Schnetter

Last modified: Tue Feb 15 2011