Resolving Multiphase Gas Production in the kpc-Scale Intergalactic Medium

          @misc{ pirsa_PIRSA:25070027,
            doi = {10.48660/25070027},
            url = {https://pirsa.org/25070027},
            author = {Willard, Charles},
            keywords = {Cosmology},
            language = {en},
            title = {Resolving Multiphase Gas Production in the kpc-Scale Intergalactic Medium},
            publisher = {Perimeter Institute},
            year = {2025},
            month = {jul},
            note = {PIRSA:25070027 see, \url{https://pirsa.org}}
          }
          

Abstract

The ultra-diffuse nature of the Intergalactic Medium (IGM) makes it inherently difficult to resolve at high spatial resolution in simulations. Typical cosmological simulations are resolution limited by large box sizes (L > 50 Mpc) used to capture accurate statistical properties of large-scale structure, while higher-resolution zoom-in simulations rarely focus on the IGM. Thus, few simulations to date resolve IGM gas at sub-kpc scales, leaving potentially important scales for gas physics unresolved. We present semi-idealized simulations of cosmic sheet collapse at higher resolutions than previously explored to study the substructure and characteristics of IGM gas. We introduce a small 1D density perturbation to the initial conditions, allowing us to use small box volumes (L = 4-8 cMpc) to resolve IGM gas at kpc scales. We confirm previous work suggesting the IGM is inherently multiphase due to cooling-based instabilities causing fragmentation. We explore how IGM multiphase fragmentation manifests with both changing resolution and sheet-virial mass/temperature. With increasing resolution, we observe enhanced neutral hydrogen column densities through the cosmic sheet. Similar to subgrid-feedback physics, the unknown effects of resolution-limited cooling instabilities represent a fundamental limitation in our understanding of diffuse baryons in the universe. We aim to quantify this phenomenon and its broader implications for Lyman limit system statistics and the Lyman-alpha forest.