Abstract: The discoveries of a number of binary black hole mergers by LIGO and VIRGO have reinvigorated the interest that primordial black holes (PBHs) of tens of solar masses could contribute non-negligibly to the dark matter energy density. Should even a small population of PBHs with masses greater than or similar to O(M-circle dot) exist, they could profoundly impact the properties of the intergalactic medium and provide insight into novel processes at work in the early Universe. We demonstrate here that observations of the 21-cm transition in neutral hydrogen during the epochs of reionization and cosmic dawn will likely provide one of the most stringent tests of solar mass PBHs. In the context of 21-cm cosmology, PBHs give rise to three distinct observable effects: (i) the modification to the primordial power spectrum (and thus also the halo mass function) induced by Poisson noise, (ii) a uniform heating and ionization of the intergalactic medium via x-rays produced during accretion, and (iii) a local modification to the temperature and density of the ambient medium surrounding isolated PBHs. Using a four-parameter astrophysical model, we show that experiments like SKA and HERA could potentially improve upon existing constraints derived using observations of the cosmic microwave background by more than 1 order of magnitude.

Abstract: We present the Cosmology and Astrophysics with Machine Learning Simulations (CAMELS) Multifield Data set (CMD), a collection of hundreds of thousands of 2D maps and 3D grids containing many different properties of cosmic gas, dark matter, and stars from more than 2000 distinct simulated universes at several cosmic times. The 2D maps and 3D grids represent cosmic regions that span similar to 100 million light-years and have been generated from thousands of state-of-the-art hydrodynamic and gravity-only N-body simulations from the CAMELS project. Designed to train machine-learning models, CMD is the largest data set of its kind containing more than 70 TB of data. In this paper we describe CMD in detail and outline a few of its applications. We focus our attention on one such task, parameter inference, formulating the problems we face as a challenge to the community. We release all data and provide further technical details at https://camels-multifield-dataset.readthedocs.io.

Abstract: In models with dark matter made of particles with keV masses, such as a sterile neutrino, small-scale density perturbations are suppressed, delaying the period at which the lowest mass galaxies are formed and therefore shifting the reionization processes to later epochs. In this study, focusing on Warm Dark Matter (WDM) with masses close to its present lower bound, i.e., around the 3. keV region, we derive constraints from galaxy luminosity functions, the ionization history and the Gunn-Peterson effect. We show that even if star formation efficiency in the simulations is adjusted to match the observed UV galaxy luminosity functions in both CDM and WDM models, the full distribution of Gunn-Peterson optical depth retains the strong signature of delayed reionization in the WDM model. However, until the star formation and stellar feedback model used in modern galaxy formation simulations is constrained better, any conclusions on the nature of dark matter derived from reionization observables remain model-dependent.