Rapport (Rapport Contrat/Projet) Année : 2026

Cerfacs ALGO Team Scientific Activity Report for the year 2025

Rapport d'activité de l'équipe ALGO du Cerfacs pour l'année 2025

Résumé

The Algo team at Cerfacs develops robust, efficient, and scalable numerical methods and designs their parallel implementation on modern scientific computing architectures. The diversity of backgrounds in applied mathematics within the team enables the Algo team to address a broad range of scientific topics. A long-standing and key research area is numerical linear algebra, with a particular emphasis on preconditioning and subspace methods for the solution of large-scale linear systems including saddle point problems, using multigrid approaches, randomized techniques, and mixed-precision computing, among others. Data Assimilation is also an important research topic within the team, where expertise in numerical linear algebra and scientific computing is leveraged to develop methods and algorithms for variational data assimilation, ensemble-based approaches, and hybrid formulations. These developments are primarily motivated by large-scale, high-dimensional problems arising in Earth system modelling and forecasting. The team’s activities further extend to uncertainty quantification in high-dimensional settings, including the estimation and representation of error covariances, as well as multi-level and multi-fidelity approaches. The Algo team is also active in scientific machine learning (SciML), with contributions to differentiable solvers, AI-based numerical methods, and hybrid strategies combining data assimilation and machine learning. More recently, the team has initiated research activities in quantum computing algorithms for fault-tolerant quantum machines, with a particular focus on algorithms for the solution of partial differential equations. Much of the research is carried out in collaboration with other Cerfacs teams, as well as with research groups in academia, industry, and operational forecasting centres at the local, national, and international levels. The Algo team members contribute to the research activities of CECI (UMR with Cerfacs, CNRS and IRD) and the joint Inria team-project Concace between Airbus CR\&T, Cerfacs and Inria.

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Dates et versions

hal-05519493 , version 1 (19-02-2026)
hal-05519493 , version 2 (23-02-2026)

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Identifiants

  • HAL Id : hal-05519493 , version 2

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Luciano Drozda Dantas Martins, Luc Giraud, Selime Gürol, Carola Kruse, Paul Mycek, et al.. Cerfacs ALGO Team Scientific Activity Report for the year 2025. TR/PA/26/6, Cerfacs - Toulouse, France. 2026. ⟨hal-05519493v2⟩
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