New Einstein Toolkit Release (Schwarzschild) - Users

24 May 2023


      Release Announcement
Click here to read the announcement in HTML (with hyperlinks):
https://einsteintoolkit.org/about/releases/ET_2023_05_announcement.html
We are pleased to announce the twenty-sixth release (code name "Karl
Schwarzschild") of the Einstein Toolkit, an open-source,
community-developed software infrastructure for relativistic
astrophysics. The major changes in this release include:
* kuibit 1.4.0, which, in addition to bug fixes, improves support
   for working with horizon data, timer data, and higher rank objects
   (See release notes for more details).
Two new arrangements and thorns have been added:
* The FUKA reader for numerical relativity initial data
 * TwoPunctures_BBHSF for binary black hole with scalar fields
   initial data
New capabilities for existing codes:
* Baikal and BaikalVacuum have been updated to have READ/WRITE
   declarations for automated ghost zone synchronization. Several
   variable groups (such as RHS variables) are also no longer
   included in checkpoint/restart operations.
 * particle_tracerET can now output the particles' four-velocity
   (contravariant and covariant); added support for binary output
   format; removed limit on the number of tracer particles
In addition, bug fixes accumulated since the previous release in
November 2022 have been included.
The Einstein Toolkit is a collection of software components and tools
for simulating and analyzing general relativistic astrophysical systems
that builds on numerous software efforts in the numerical relativity
community, including code to compute initial data parameters, the
spacetime evolution codes Baikal, lean_public, and McLachlan, analysis
codes to compute horizon characteristics and gravitational waves, the
Carpet AMR infrastructure, and the relativistic magneto-hydrodynamics
codes GRHydro and IllinoisGRMHD. Data analysis and post-processing is
handled by the kuibit library. The Einstein Toolkit also contains a 1D
self-force code. For parts of the toolkit, the Cactus Framework is used
as the underlying computational infrastructure, providing large-scale
parallelization, general computational components, and a model for
collaborative, portable code development.
The Einstein Toolkit uses a distributed software model, and its
different modules are developed, distributed, and supported either by
the core team of Einstein Toolkit Maintainers or by individual groups.
Where modules are provided by external groups, the Einstein Toolkit
Maintainers provide quality control for modules for inclusion in the
toolkit and help coordinate support. The Einstein Toolkit Maintainers
currently involve staff and faculty from five different institutions and
host weekly meetings that are open for anyone to join.
Guiding principles for the design and implementation of the toolkit
include: open, community-driven software development; well thought-out
and stable interfaces; separation of physics software from computational
science infrastructure; provision of complete working production code;
training and education for a new generation of researchers.
For more information about using or contributing to the Einstein
Toolkit, or to join the Einstein Toolkit Consortium, please visit our
web pages at http://einsteintoolkit.org, or contact the users mailing
list users@einsteintoolkit.org.
The Einstein Toolkit is primarily supported by NSF
2004157/2004044/2004311/2004879/2003893 (Enabling fundamental research
in the era of multi-messenger astrophysics).
The Einstein Toolkit contains about 350 regression test cases. On a
large portion of the tested machines, almost all of these tests pass,
using both MPI and OpenMP parallelization.
Deprecated functionality
There are no features marked as deprecated in this release, to be
removed in the next release.
Contributors
Among the many contributors to the Einstein Toolkit and to this release
in particular, important contributions to new components were made by
the following authors:
* Cheng-Hsin Cheng
 * Gabriele Bozzola
 * Leonardo Werneck
 * Ludwig Jens Papenfort
 * Samuel Cupp
 * Samuel Tootle
How to upgrade from Kowalevski Release (ET_2022_11)
To upgrade from the previous release, use GetComponents with the new
thornlist to check out the new version.
See the Download page (http://einsteintoolkit.org/download.html) on the
Einstein Toolkit website for download instructions.
The SelfForce-1D code uses a single git repository; thus, using
git pull; git checkout ET_2023_05
will update the code.
To install Kuibit, do the following:
pip install --user -U kuibit==1.4.0
Machine notes
Supported (tested) machines include:
* Debian, Ubuntu, Fedora, Mint, OpenSUSE, and macOS X installations
   with dependencies installed as prescribed in the official
   installation instructions
 * Deep Bayou
 * Delta
 * Expanse
 * Frontera
 * Golub
 * Queen Bee 2
 * Queen Bee 3
 * Stampede 2
 * Summit
 * Sunrise
 * SuperMIC
 * SuperMUC
 * ThornyFlat
Note for individual machines:
* TACC machines: defs.local.ini needs to have `sourcebasedir =
   $WORK` and `basedir = $SCRATCH/simulations` configured for this
   machine. You need to determine $WORK and $SCRATCH by logging in to
   the machine.
 * SuperMUC-NG: defs.local.ini needs to have `sourcebasedir = $HOME`
   and `basedir = $SCRATCH/simulations` configured for this machine.
   You need to determine $HOME and $SCRATCH by logging in to the
   machine.
All repositories participating in this release carry a branch ET_2023_05
marking this release. These release branches will be updated if severe
errors are found.
The "Karl Schwarzschild" Release Team on behalf of the Einstein Toolkit
Consortium (2023-05-24)
* Leonardo Werneck
 * Samuel Cupp
 * Beyhan Karakas
 * Bing-Jyun Tsao
 * Cheng-Hsin Cheng
 * Jake Doherty
 * Konrad Topolski
 * Peter Diener
 * Roland Haas
 * Steven R. Brandt
 * Terrence Pierre Jacques
 * Thiago Assumpcao
 * Zachariah Etienne
May 24, 2023