Theoretical Modeling of Large-Scale Structure of the Universe

Session

Simulations and theory interplay

4 Jun 2024, 09:00

Lecture Theatre

13. Fast numerical methods for cosmological inference from LSS (Hahn)

04/06/2024, 09:00

14. Hermes - Towards an Ultimate High-Performance Algorithm for Cosmic Statistics of Large Data Sets (Feng)

04/06/2024, 09:30

Motivated by demanding a fast algorithm of cosmic statistics to tackle extremely large data sets from ongoing and upcoming galaxy surveys, we make the first release of Hermes (HypER-speed MultirEsolution cosmic Statistics), an open-source parallel/GPU-accelerated Python package. The core algorithm implemented in the Hermes Python package is based on the MRA-CS (MultiResolution Analysis -...

15. CLASS-OneLoop: Presentation and mock data analysis (Linde)

04/06/2024, 09:47

We present CLASS-OneLoop, a numerical tool fully integrated into the Boltzmann code CLASS, enabling the calculation of the one-loop power spectrum of biased tracers in redshift space following the EFTofLSS. We first summarise the theoretical modelling and the expansion formalism used in the code. We then show that an MCMC fit to spectrum wedges measured from the AbacusSummit suite with...

16. CLASS-OneLoop: Numerical Implementation and Outlook (Lesgourgues)

04/06/2024, 10:17

In this follow-up talk, we provide details on the CLASS-OneLoop module: overall structure, input options, estimated accuracy, validation against CLASS-PT, algorithms and strategies for efficient loop integrals, and overall performances.

17. Predicting non-linear effects in matter clustering from changes in cosmology and baryons using multi-fidelity simulations (Conley)

04/06/2024, 11:04

Cosmological simulations provide a powerful framework for investigating the non-linear growth and evolution of large-scale structure (LSS) in the Universe. This research addresses the challenges of understanding how large scale structure is affected by both cosmology and astrophysics with the aim of making precise predictions of observables such as the cosmic shear and galaxy clustering for...

18. The “Missing baryons” in the cosmic web—what is it? Where is it? How much? (Ma)

04/06/2024, 11:21

Previous studies of galaxy formation have shown that only 10 per cent of the cosmic baryons are in stars and galaxies, while 90 per cent of them are missing. In this talk, I will present three observational studies that coherently find significant evidences of the missing baryons. The first is the cross-correlation between the kinetic Sunyaev-Zeldovich maps from Planck with the linear...

20. Hybrid Lagrangian models (Zennaro)

04/06/2024, 11:38

Emulators are becoming increasingly important in performing Bayesian inference for current and upcoming cosmological surveys. I will discuss the hybrid Lagrangian bias expansion model in real space, a nonlinear bias model able to describe galaxy clustering to very small scales (~0.7 h/Mpc) and its corresponding emulator implementation in the emulation suite baccoemu. I will also quickly review...

19. HYMALAIA: A Hybrid Lagrangian Model for Intrinsic Alignments (Maion)

04/06/2024, 12:08

The intrinsic alignment of galaxies is an important ingredient for modelling weak-lensing measurements, and a potentially valuable cosmological and astrophysical signal. In this talk, I will present HYMALAIA: a new model to predict the intrinsic alignments of biased tracers. HYMALAIA is based on a perturbative expansion of the statistics of the Lagrangian shapes of objects, which is then...

21. Extending Hybrid Models of structure formation (Pellejero)

04/06/2024, 13:38

Hybrid models use the displacement field generated by N-body simulations to precisely forecast structure formation. The distribution of galaxies is then computed employing a bias expansion technique rooted in the symmetries of galaxy formation physics. This methodology has demonstrated its ability to yield unbiased cosmological constraints across various investigations. Nonetheless, it...

22. Field-level emulation of cosmic structure formation with styled neural networks (Jamieson)

04/06/2024, 14:08

Surveying the large-scale structure of the universe will yield an enormous amount of high-quality data for constraining cosmology and potentially detecting new physics. Extracting the maximum amount of information from this dataset and using it to its full potential requires fast and accurate cosmic structure formation simulations. N-body simulations deliver a high level of accuracy but are...

23. Perturbative Forward-Modeling of Large-Scale Structure for Field-Level Analysis and Beyond (Stadler)

04/06/2024, 14:25

The forthcoming high-quality data from the next generation of galaxy surveys promises powerful new tests of cosmology. However, fully realizing this potential poses new challenges in theoretical modeling and analysis. Novel analysis techniques are required to maximize the cosmological information extracted from the data while remaining robust to theoretical uncertainties in the small-scale...

24. How much information is left in galaxy clustering beyond the power spectrum? (Akitsu)

04/06/2024, 15:30

I will talk about the field-level inference of galaxy clustering with perturbative forward modeling, focusing on the information content beyond the power spectrum. I may also discuss the equivalence (and possible difference) of biasing scheme in the polyspectra and the field-level.