Pushing field level inference into the non-linear regime with multi-probe analysis

          @misc{ scivideos_PIRSA:26060027,
            doi = {10.48660/26060027},
            url = {https://pirsa.org/26060027},
            author = {Horowitz, Benjamin},
            keywords = {Cosmology},
            language = {en},
            title = {Pushing field level inference into the non-linear regime with multi-probe analysis},
            publisher = {Perimeter Institute for Theoretical Physics},
            year = {2026},
            month = {jun},
            note = {PIRSA:26060027 see, \url{https://scivideos.org/pirsa/26060027}}
          }
          

Abstract

Understanding the complex interplay of gas and dark matter is critical for the next generation of cosmological surveys and related inference. While many techniques seek to marginalize over these uncertainties, there is a wealth of information from across astrophysics than can better constrain properties like galaxy formation and evolution. In this talk, I will introduce recent developments in pushing field level inference into these nonlinear scales. These efforts include differentiable models for full dark-matter dynamics (i.e. TreePM), hydrodynamical physics, subgrid physics, and halos/group finding. Not only can differentiability be used for explicit likelihood analysis, but also to greatly accelerate existing simulation-based pipelines. Time permitting, I will also discuss how these techniques will be used for an integrated analysis in the ongoing Prime Focus Spectrograph survey, which will study galaxy evolution from z ~ 7.2 to the present day.