This project aims to enhance the synergy between astronomical observations, numerical cosmological simulations and galaxy modelling. Upcoming instruments like Euclid, DESI and Rubin LSST, among others, will make wide-field galaxy surveys with extremely precise measurements. The enhanced precision in the observations however, will requite robust theoretical predictions from galaxy formation models to achieve a profound understanding of the fundamental physics underlying the cosmological measurements.

To achieve this, exa-supercomputers will play a key role. Unlike modern supercomputers, which typically consist of thousands of CPUs for state-of-the-art simulation productions, exa-supercomputers will employ a hybrid configuration of CPUs hosts with GPUs accelerators. This configuration will empower the computations of up to 10^18 operations per second. Exa-supercomputers will revolutionise our ability to simulate cosmological volumes spanning 4 Gigaparsecs (Gpc) with 25 trillion particles! the minimum volume and resolution requirements necessary for making predictions of Euclid data.

However, the challenge to-date lies in the fact that cosmological simulation software designed for exa-supercomputers lacks the modelling for galaxy formation. Examples include the HACC-CRKSPH code (Habib et al. 2016, Emberson et al. 2019) and PKDGRAV3 (Potter, Stadel & Teyssier 2017), that have produced the largest simulations to-date, FarPoint (Frontiere et al. 2022), encompassing 1.86 trillion particles within a 1 Gpc volume, and Euclid Flagship (Potter, Stadel & Teyssier 2017), featuring 2 trillion particles in a 3 Gpc volume, respectively. While HACC-CRKSPH and PKDGRAV3 were developed to run on modern GPUs-accelerated supercomputers, they lack the complex physics of galaxy formation and can therefore only produce gravity-only cosmological boxes.

The SWIFT code (Schaller et al. 2023) is a parallel effort that has produced Flamingo (Schaye et al. 2023), the largest simulation that integrates gravity, hydrodynamics and galaxy formation physics, encompassing 0.3 trillion particles. However, the caveat of SWIFT is that it was primarily designed for CPU usage. The adaptation of SWIFT to run on modern GPUs will require the entire redevelopment of the code. Another example are the current big simulations of galaxy formation done at Irfu, such as Extreme Horizon (Chabanier et al. 2020), that have also reached their limit as they rely on CPU-based codes that hamper their scalability.

Understanding the intricacies of galaxy formation is paramount for interpreting astronomical observations. In this pursuit, CEA DRF/Irfu stands uniquely positioned to lead the advances in astrophysics in the emerging exascale era. Researchers at DAp and DPhP have already embarked on the analysis of high-quality data from the Euclid mission and DESI. Simultaneously, a team at DEDIP is developing DYABLO (Durocher & Delorme, in preparation), a robust gravity + hydrodynamics code tailored explicitly for exa-supercomputing.

In recent years, significant investments have been channeled into the advancement of DYABLO. Numerous researchers at DAp and DEDIP have contributed on various aspects (from the hydrodynamics of solar physics to refining Input/Output processes) thanks to collaborative grants such as PTC-CEA grant and FETHPC European project IO-SEA. Additionally, DYABLO has benefited from interactions with CEA research unit, Maison de la simulation (CEA & CNRS).

This ambitious project aims to extend DYABLO's capabilities by integrating galaxy formation modules in collaboration with Maxime Delorme. These modules will encompass radiative gas cooling and heating, star formation, chemical enrichment, stellar mass loss, energy feedback, black holes, and active galactic nuclei feedback. The ultimate objective is to enhance the analysis of Euclid and DESI data by generating simulation predictions of galaxy formation and evolution using DYABLO. The initial dataset will involve a comprehensive examination of clustering of matter and galaxy clustering, in partnership with researchers at DAp/LCEG and DAp/CosmoStat.

This thesis will create the first version of a galaxy formation code optimised for exa-scale supercomputing. Ongoing developments will not only expand its capabilities but also unlock new opportunities for in-depth research, enhancing synergy between astronomical observations, numerical cosmological simulations, and galaxy modelling.

References:
Habib, S., et al., 2016, New Astronomy, Volume 42, p. 49-65.
Emberson, J.D., et al., 2019, The Astrophysical Journal, Volume 877, Issue 2, article id. 85, 17 pp.
Potter, D., Stadel, J., & Teyssier, R., 2017, Computational Astrophysics and Cosmology, Vol. 4, Issue 1, 13 pp.
Frontiere, N., et al., 2023, The Astrophysical Journal Supplement Series, Volume 264, Issue 2, 24 pp.
Schaller, M., et al., 2023, eprint arXiv:2305.13380
Schaye, J., et al., 2023, eprint arXiv:2306.04024
Chabanier, S., et al., 2020, Astronomy & Astrophysics, Volume 643, id. L8, 12 pp.