[Users] ET_2023_11 "Lise Meisner" Einstein Toolkit Release Announcement

[Cupp, Samuel D.]

Release Announcement

Click here to read the announcement in HTML (with hyperlinks):
https://einsteintoolkit.org/about/releases/ET_2023_11_announcement.html

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

Several new arrangements and thorns have been added:

 * CarpetX arrangement for the new AMReX-based mesh driver and
   supporting thorns
 * GRHayLib for access to the General Relativistic Hydrodynamics
   Library (GRHayL)
 * GRHayLID for simple GR(M)HD initial data using GRHayLib (e.g.
   Balsara tests, isotropic gas)
 * GRHayLHD for GRHD evolution using GRHayL (equivalent to
   IllinoisGRMHD with no magnetic fields)
 * GRHayLIDX for CarpetX version of GRHayLID; this thorn currently
   runs on the host, not the gpu
 * GRHayLHDX for CarpetX version of GRHayLHD; this thorn currently
   runs on the host, not the gpu
 * DNSdata for importing SGRID initial data

New capabilities for existing codes:

 * Seed_Magnetic_Fields has been updated to support both TOV and BNS
   magnetic fields; explicit IllinoisGRMHD scheduling dependency
   removed to support broader usage; some parameter options are
   deprecated and will be removed in the next release

In addition, bug fixes accumulated since the previous release in May
2023 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 GRHayLHD, GRHayLHDX, 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 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
 * Seed_Magnetic_Fields: to support the changes, parameter options
   were renamed; the old options are deprecated and will be removed
   in the next release
 * Seed_Magnetic_Fields_BNS is slated to be removed in the next
   release, as its features have been merged into
   Seed_Magnetic_Fields

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:

 * Federico G. Lopez Armengol
 * Steven R. Brandt
 * Michail Chabanov
 * Cheng-Hsin Cheng
 * Samuel Cupp
 * Alexandru Dima
 * Jake Doherty
 * Lorenzo Ennoggi
 * Zachariah Etienne
 * Roland Haas
 * Terrence Pierre Jacques
 * Liwei Ji
 * Jay Kalinani
 * Philipp Moesta
 * Michal Pirog
 * Lucas Timotheo Sanches
 * Erik Schnetter
 * Swapnil Shankar
 * Wolfgang Tichy
 * Leonardo Werneck

How to upgrade from Schwarzschild Release (ET_2023_05)

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_11

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
 * Anvil
 * Deep Bayou
 * 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_2023_11
marking this release. These release branches will be updated if severe
errors are found.

The "Lise Meitner" Release Team on behalf of the Einstein Toolkit
Consortium (2023-12-14)

 * Samuel Cupp
 * Steven R. Brandt
 * Peter Diener
 * Zachariah Etienne
 * Roland Haas
 * Liwei Ji
 * Deborah Ferguson
 * Gabriele Bozzola
 * Hyun Park

December 14, 2023
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