N-body simulation-based templates, so-called emulators, will enable us to accurately predict dark matter halo properties down to highly non-linear scales. This talk presents an accurate and flexible emulated-based halo model for the real- and redshift-space galaxy two-point correlation functions. The main set of simulations — the FORGE modified gravity N-body simulation suite — covers 50 cosmologies around the Planck ΛCDM cosmology in f(R) gravity. We feed the data into neural networks to emulate the halo mass functions (HMFs), halo concentration-mass relations, halo real-space clustering and pairwise velocity moments. For example, the emulator for HMFs achieves about 1% accuracies. Once the halo emulators are ready, we will have the flexibility to combine them with a viable galaxy-halo connection model, such as the halo occupation distribution, to compute galaxy two-point correlation functions. In the end, we demonstrate that this halo model approach can be applied to describe the cosmological observables beyond two-point statistics and galaxy clustering.
This Friday colloquium will be hybrid. Attendees can therefore participate either in-person or via Zoom. Please join via Zoom at
https://uio.zoom.us/j/69001043754?pwd=cEJpbVE5ci9PdWNtRld2TDNNcGtKdz09
Meeting ID:690 0104 3754
Passcode: PeiseStua3
Attendees will be muted during the colloquium, but will have the opportunity to ask questions at the end by clicking on the "raise hand” button (or send a request via chat).