Beschreibung
A question that has gained importance in recent years is how to maximize the cosmological information that can be extracted from observational data.
Approaches based on summary statistics compress the data into a lower-dimensional representation, thereby losing part of the information. In contrast, the core idea of field-level inference is to use the full overdensity field, bypassing the compression step entirely.
The LEFTfield code has been developed to enable this type of inference. Given some initial conditions, it computes the galaxy overdensity field at a desired redshift using Lagrangian Perturbation Theory (LPT) supplemented with Lagrangian or Eulerian implementation of galaxy bias. To ensure unbiased results, it is necessary to include in the forward modeling all relevant physical effects present in observed data; among these, the impact of massive neutrinos plays a central role.
Since neutrinos do not fit naturally into the analytical framework of LPT, alternative approaches are required to model their effects accurately. In this talk, I will present a first solution for implementing massive neutrinos in LEFTfield, opening the way to measuring neutrino masses from field-level data.