The Manticore Universe and its Applications to Cosmology

About

Traditional summary statistics such as the N‑point correlation function have long been the backbone of cosmological inference, yielding tight constraints on the standard model and its parameters. Yet the incremental gains in precision have largely mirrored the expansion of survey volume rather than advances in modelling at galactic scales, leaving the wealth of small‑scale information largely untapped. In this talk I will introduce a promising alternative that seeks to bridge this gap: field‑level inference of the primordial density field. By jointly modelling the full three‑dimensional density field and its evolution, this approach allows us to exploit the full statistical power of current surveys, even in the presence of complex selection effects and observational systematics.

Our group has recently achieved a landmark result with the release of the Manticore Data products. These data sets comprise high‑fidelity reconstructions of the initial conditions that give rise to the observed large‑scale structure, derived from a combination of spectroscopic galaxy surveys and complementary probes. I will walk through the methodology used to generate the Manticore reconstructions, highlighting how we incorporate galaxy bias, redshift‑space distortions, and nonlinear gravitational evolution within a Bayesian forward‑modelling framework. I will then illustrate how the reconstructed fields can be employed to constrain a variety of cosmological observables: the Hubble constant $H_{0}$, the calibration of X‑ray and SZ mass proxies, and the annihilation cross‑section of dark matter particles. .

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