ARES (Algorithm for REconstruction and Sampling)

• Tool name , objectives, feature:

ARES is a flexible, and computationally efficient framework for a joint estimation of the large-scale structure and its power-spectrum, building on a Gibbs sampling framework. The ARES framework is based on Gaussian statistics and lays the foundation of the BORG framework. ARES is designed reconstruct the 3D power-spectrum together with the underlying dark matter density field in a Bayesian framework, under the reasonable assumption that the long wave-length Fourier components are Gaussian distributed.

• contact (person witin ADE, ie. that can help, not necessarily author): Guilhem Lavaux
• author(s): The Aquila Consortium
• publication(s), refs:

Jasche & Lavaux (2014), Jaschet et al. (2010)

• main url (if any): https://www.aquila-consortium.org
• documentation (if any) :

https://big4.iap.fr, https://www.aquila-consortium.org

• type: Library and Application
• language: C++
• parallelism: OpenMP, MPI
• ressources required: Mesocenter and Supercomputers
• availability: