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Villanueva-Domingo, P., Mena, O., & Miralda-Escude, J. (2020). Maximum amplitude of the high-redshift 21-cm absorption feature. Phys. Rev. D, 101(8), 083502–8pp.
Abstract: We examine the maximum possible strength of the global 21-cm absorption dip on the cosmic background radiation at high-redshift caused by the atomic intergalactic medium, when the Lyman-alpha coupling is maximum, assuming no exotic cooling mechanisms from interactions with dark matter. This maximum absorption is limited by three inevitable factors that need to be accounted for: (a) heating by energy transferred from the cosmic background radiation to the hydrogen atoms via 21-cm transitions, dubbed as 21-cm heating; (b) Ly alpha heating by scatterings of Ly alpha photons from the first stars; (c) the impact of the expected density fluctuations in the intergalactic gas in standard cold dark matter theory, which reduces the mean 21-cm absorption signal. Inclusion of this third novel effect reduces the maximum global 21-cm absorption by similar to 10%. Overall, the three effects studied here reduce the 21-cm global absorption by similar to 20% at z similar or equal to 17.
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Villanueva-Domingo, P., & Ichiki, K. (2023). 21 cm forest constraints on primordial black holes. Publ. Astron. Soc. Jpn., 75(SP1), S33–S49.
Abstract: Primordial black holes (PBHs) as part of the dark matter (DM) would modify the evolution of large-scale structures and the thermal history of the universe. Future 21 cm forest observations, sensitive to small scales and the thermal state of the intergalactic medium (IGM), could probe the existence of such PBHs. In this article, we show that the shot noise isocurvature mode on small scales induced by the presence of PBHs can enhance the amount of low-mass halos, or minihalos, and thus, the number of 21 cm absorption lines. However, if the mass of PBHs is as large as M-PBH greater than or similar to 10 M-circle dot, with an abundant enough fraction of PBHs as DM, f(PBH), the IGM heating due to accretion on to the PBHs counteracts the enhancement due to the isocurvature mode, reducing the number of absorption lines instead. The concurrence of both effects imprints distinctive signatures on the number of absorbers, allowing the abundance of PBHs to be bound. We compute the prospects for constraining PBHs with future 21 cm forest observations, finding achievable competitive upper limits on the abundance as low as f(PBH) similar to 10(-3) at M-PBH = 100 M-circle dot, or even lower at larger masses, in regions of the parameter space unexplored by current probes. The impact of astrophysical X-ray sources on the IGM temperature is also studied, which could potentially weaken the bounds.
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Villanueva-Domingo, P., Gnedin, N. Y., & Mena, O. (2018). Warm Dark Matter and Cosmic Reionization. Astrophys. J., 852(2), 139–7pp.
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.
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Villanueva-Domingo, P., Gariazzo, S., Gnedin, N. Y., & Mena, O. (2018). Was there an early reionization component in our universe? J. Cosmol. Astropart. Phys., 04(4), 024–17pp.
Abstract: A deep understanding of the epoch of reionization is still missing in our knowledge of the universe. While future probes will allow us to test the precise evolution of the free electron fraction from redshifts between z similar or equal to 6 and z similar or equal to 20, at present one could ask what kind of reionization processes are allowed by present cosmic microwave background temperature and polarization measurements. An early contribution to reionization could imply a departure from the standard picture where star formation determines the reionization onset. By considering a broad class of possible reionization parameterizations, we find that current data do not require an early reionization component in our universe and that only one marginal class of models, based on a particular realization of reionization, may point to that. In addition, the frequentist Akaike information criterion (AIC) provides strong evidence against alternative reionization histories, favoring the most simple reionization scenario, which describes reionization by means of only one (constant) reionization optical depth tau.
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Villaescusa-Navarro, F. et al, & Villanueva-Domingo, P. (2022). The CAMELS Multifield Data Set: Learning the Universe's Fundamental Parameters with Artificial Intelligence. Astrophys. J. Suppl. Ser., 259(2), 61–14pp.
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.
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