ARES is the main component of the Bayesian Large Scale Structure inference pipeline. The present version of the ARES framework is 2.1. Please consult the Release notes for an overview of the different improvements over the different versions.

ARES is written in C++14 and has been parallelized with OpenMP and MPI. It currently compiles with major compilers (gcc, intel, clang).

Build status Made with C++ & Python Check readthedocs.org

Citing

If you are using ARES for your project, please cite the following articles for ARES2, ARES3 and BORG3:

  • Jasche, Kitaura, Wandelt, 2010, MNRAS, 406, 1 (arxiv 0911.2493)

  • Jasche & Lavaux, 2015, MNRAS, 447, 2 (arxiv 1402.1763)

  • Lavaux & Jasche, 2016, MNRAS, 455, 3 (arxiv 1509.05040)

  • Jasche & Lavaux, 2019, A&A, 625, A64 (arxiv 1806.11117)

HADES and BORG papers have a different listing.

For a full listing of publications from the Aquila consortium, please check the Aquila website.

Acknowledgements

This work has been funded by parts by the following grants and institutions over the years:

  • The DFG cluster of excellence “Origin and Structure of the Universe” (http://www.universe-cluster.de). The Excellence cluster funded the salaries of a few individual ona case by case basis, as well as the buying of equipments;

  • Institut Lagrange de Paris (grant ANR-10-LABX-63, http://ilp.upmc.fr) within the context of the Idex SUPER subsidized by the French government through the Agence Nationale de la Recherche (ANR-11-IDEX-0004-02). ILP has funded the salaries of some post-doc and PhD student and provided travel grants;

  • The BIG4 project funded by the ANR (ANR-16-CE23-0002) (https://big4.iap.fr);

  • The “Programme National de Cosmologie et Galaxies” (PNCG, CNRS/INSU) for some of the early developments;

  • Through the grant code ORIGIN, it has received support from the “Domaine d’Interet Majeur (DIM) Astrophysique et Conditions d’Apparitions de la Vie (ACAV)” from Ile-de-France region. It has allowed notably access to computational hardware at IAP.

  • The Starting Grant (ERC-2015-STG 678652) “GrInflaGal” of the European Research Council.