Field-Level Inference of Primordial Non-Gaussianity

June 10, 2026 PIRSA:26060050 Conference Cosmology

Conference/School: Advancing Field-level and Simulation-based Inference for Cosmology

Simon, H. (2026). Field-Level Inference of Primordial Non-Gaussianity. Perimeter Institute. https://pirsa.org/26060050

Simon, Hugo. Field-Level Inference of Primordial Non-Gaussianity. Perimeter Institute, Jun. 10, 2026, https://pirsa.org/26060050

@misc{ pirsa_PIRSA:26060050,
  doi = {10.48660/26060050},
  url = {https://pirsa.org/26060050},
  author = {Simon, Hugo},
  keywords = {Cosmology},
  language = {en},
  title = {Field-Level Inference of Primordial Non-Gaussianity},
  publisher = {Perimeter Institute},
  year = {2026},
  month = {jun},
  note = {PIRSA:26060050 see, \url{https://pirsa.org}}
}

Abstract

Field-Level Inference (FLI) needs to be made more tractable and robust at survey scale. To this purpose, I developed fast, differentiable cosmological simulators and introduced a standardized benchmark, showing how to reduce the required model evaluations by orders of magnitude. Building on this, I am working toward FLI constraints on local Primordial Non-Gaussianity (PNG) from DESI. I will show the validation of the pipeline on N-body simulations with HOD-populated galaxies, carefully assessing model fidelity and calibration, progressively incorporating survey realism at the field-level, and in parallel extending the analysis to a multi-probe framework combining galaxy clustering with CMB lensing.