A Point-Transformed Gaussian Model for Field-Level Mass Distributions in Tomographic Density Slabs

          @misc{ scivideos_PIRSA:26060036,
            doi = {10.48660/26060036},
            url = {https://pirsa.org/26060036},
            author = {Tong, Alexander},
            keywords = {Cosmology},
            language = {en},
            title = {A Point-Transformed Gaussian Model for Field-Level Mass Distributions in Tomographic Density Slabs},
            publisher = {Perimeter Institute for Theoretical Physics},
            year = {2026},
            month = {jun},
            note = {PIRSA:26060036 see, \url{https://scivideos.org/pirsa/26060036}}
          }
          

Abstract

The work presented in this talk is part of a program of performing field-level cosmological analyses using galaxy and weak lensing observables in density slabs of $O[100\ \mathrm{Mpc}]$. The inference pipeline requires a model for the mass overdensity field which is accurate to scales of a few Mpc across cosmologies, and also fast in the generation of sample fields. I will describe a scheme in which the nonlinear mass overdensity field is obtained by applying some point transformation to a Gaussian random field. I will present our transformation function that, with a small number of parameters, characterizes the mass distribution in a slab for different redshifts, slab widths, and cosmologies. I will show that the model accurately reproduces the statistical properties of mass overdensity fields from Gower Street simulations, demonstrating its viability for field-level inference. Finally, I will discuss a validation test which uses the point-transformed Gaussian model to infer the cosmology from the output of an $N$-body simulation.