The detection of the accelerated expansion of the Universe has been one of the major
breakthroughs in modern cosmology. Several cosmological probes (Cosmic Microwave …

The CAMELS Project: Cosmology and Astrophysics with Machine-learning Simulations -
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We present cosmological constraints from a simulation-based inference (SBI) analysis of
galaxy clustering from the SimBIG forward modeling framework. SimBIG leverages the …

We present a novel simulation-based hybrid emulator approach that maximally derives
cosmological and Halo Occupation Distribution (HOD) information from non-linear galaxy …

Optimal extraction of the non-Gaussian information encoded in the large-scale structure of
the Universe lies at the forefront of modern precision cosmology. We propose achieving this …

We revisit cosmological constraints on the sum of the neutrino masses Σ m ν from a
combination of full-shape BOSS galaxy clustering [P (k)] data and measurements of the …

Massive neutrinos suppress the growth of structure on small scales and leave an imprint on
large-scale structure that can be measured to constrain their total mass, M ν. With standard …

We train deep-learning models on thousands of galaxy catalogs from the state-of-the-art
hydrodynamic simulations of the Cosmology and Astrophysics with MachinE Learning …

We perform the first application of the wavelet scattering transform (WST) to actual galaxy
observations, through a WST analysis of the BOSS DR12 CMASS dataset. We included the …

We quantify the information content of the nonlinear matter power spectrum, the halo mass
function, and the void size function, using the Quijote N-body simulations. We find that these …