[Users] ET_2024_05 "Lev Landau" Einstein Toolkit Release Announcement

[sbrandt at cct.lsu.edu]

Release Announcement

Click here to read the announcement in HTML (with hyperlinks):
https://einsteintoolkit.org/about/releases/ET_2024_05_announcement.html

We are pleased to announce the twenty-eighth release (code name "Lev
Landau") of the Einstein Toolkit, an open-source, community-developed
software infrastructure for relativistic astrophysics. The major changes
in this release include:

One new thorn has been added:

 * NewRadX -- This thorn provides radiative outer boundaries for the
   CarpetX driver.

Updated thorns:

 * GRHayL-based IllinoisGRMHD -- this release introduces entropy
   evolution, tabulated equation of state, and piecewise polytrope
   support
 * Baikal(Vacuum) -- updated to use the new version of the Python
   code generator NRPy 2.0
 * GRHayLHD(X) -- now has a tabulated EOS
 * Kuibit -- now supports reading the OpenPMD files generated by
   CarpetX

In addition, bug fixes accumulated since the previous release in Nov
2023 have been included. Including ticket number 2647, correction to the
WENO coefficients.

The Einstein Toolkit is a collection of software components and tools
for simulating and analyzing general relativistic astrophysical systems.
It builds on numerous software efforts in the numerical relativity
community, including codes 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 GRHayLHD, GRHayLHDX, GRHydro, and IllinoisGRMHD. Data analysis and
post-processing are 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. 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 ensure quality control for modules included 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 to anyone.

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 at einsteintoolkit.org.

The Einstein Toolkit is primarily supported by NSF
2004157/2004044/2004311/2004879/2003893/2114582/2227105 (Enabling
fundamental research in the era of multi-messenger astrophysics).

The Einstein Toolkit contains about 400 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
 * Convert_to_HydroBase and ID_converter_ILGRMHD are deprecated, as
   their functionality has been incorporated into IllinoisGRMHD
 * Many IllinoisGRMHD parameters are deprecated, as they are now
   controlled by GRHayLib

Contributors

Among the many contributors to the Einstein Toolkit and to this release
in particular, important contributions to new and existing components
were made by the following authors:

 * Alexandru Dima
 * Cheng-Hsin Cheng
 * Erik Schnetter
 * Gabriele Bozzola
 * Hayley Macpherson
 * Helvi Witek
 * Jake Doherty
 * Jay Kalinani
 * Krishiv Bhatia
 * Leonardo Werneck
 * Liwei Ji
 * Lucas Timotheo Sanches
 * Michail Chabanov
 * Roland Haas
 * Samuel Cupp
 * Samuel Tootle
 * Steven R. Brandt
 * Swapnil Shankar
 * Wolfgang Tichy
 * Zach Etienne

How to upgrade from Meitner Release (ET_2023_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_2024_05

will update the code.

To install Kuibit, do the following:

pip install --user -U kuibit==1.5.0

Machine notes

Supported (tested) machines include:

 * Debian, Ubuntu, Fedora, Mint, OpenSUSE, and macOS installations
   with dependencies installed as prescribed in the official
   installation instructions
 * Anvil
 * Deep Bayou
 * Supermike
 * Queen Bee 3 and 4
 * Delta
 * Expanse
 * Frontera
 * Sunrise

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.

All repositories participating in this release carry a branch ET_2024_05
marking this release. These release branches will be updated if severe
errors are found.

The "Lev Landau" Release Team on behalf of the Einstein Toolkit
Consortium (2024-06-28)

 * Steven R. Brandt
 * Roland Haas
 * Peter Diener
 * Lorenzo Ennoggi
 * Deborah Ferguson
 * Liwei Ji
 * Jay Kalinani
 * Lucas Timotheo Sanches
 * Bing-Jyun Tsao
 * Maxwell Rizzo
 * Dhruv Srivastava
 * Terrence Pierre Jacques

June 28, 2024