Villanueva-Domingo, P., Mena, O., & Palomares-Ruiz, S. (2021). A Brief Review on Primordial Black Holes as Dark Matter. Front. Astron. Space Sci., 8, 681084–10pp.
Abstract: Primordial black holes (PBHs) represent a natural candidate for one of the components of the dark matter (DM) in the Universe. In this review, we shall discuss the basics of their formation, abundance and signatures. Some of their characteristic signals are examined, such as the emission of particles due to Hawking evaporation and the accretion of the surrounding matter, effects which could leave an impact in the evolution of the Universe and the formation of structures. The most relevant probes capable of constraining their masses and population are discussed.
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Villanueva-Domingo, P., & Villaescusa-Navarro, F. (2021). Removing Astrophysics in 21 cm Maps with Neural Networks. Astrophys. J., 907(1), 44–14pp.
Abstract: Measuring temperature fluctuations in the 21 cm signal from the epoch of reionization and the cosmic dawn is one of the most promising ways to study the universe at high redshifts. Unfortunately, the 21 cm signal is affected by both cosmology and astrophysics processes in a nontrivial manner. We run a suite of 1000 numerical simulations with different values of the main astrophysical parameters. From these simulations we produce tens of thousands of 21 cm maps at redshifts 10 <= z <= 20. We train a convolutional neural network to remove the effects of astrophysics from the 21 cm maps and output maps of the underlying matter field. We show that our model is able to generate 2D matter fields not only that resemble the true ones visually but whose statistical properties agree with the true ones within a few percent down to scales 2 Mpc(-1). We demonstrate that our neural network retains astrophysical information that can be used to constrain the value of the astrophysical parameters. Finally, we use saliency maps to try to understand which features of the 21 cm maps the network is using in order to determine the value of the astrophysical parameters.
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Villanueva-Domingo, P., Villaescusa-Navarro, F., Angles-Alcazar, D., Genel, S., Marinacci, F., Spergel, D. N., et al. (2022). Inferring Halo Masses with Graph Neural Networks. Astrophys. J., 935(1), 30–15pp.
Abstract: Understanding the halo-galaxy connection is fundamental in order to improve our knowledge on the nature and properties of dark matter. In this work, we build a model that infers the mass of a halo given the positions, velocities, stellar masses, and radii of the galaxies it hosts. In order to capture information from correlations among galaxy properties and their phase space, we use Graph Neural Networks (GNNs), which are designed to work with irregular and sparse data. We train our models on galaxies from more than 2000 state-of-the-art simulations from the Cosmology and Astrophysics with MachinE Learning Simulations project. Our model, which accounts for cosmological and astrophysical uncertainties, is able to constrain the masses of the halos with a similar to 0.2 dex accuracy. Furthermore, a GNN trained on a suite of simulations is able to preserve part of its accuracy when tested on simulations run with a different code that utilizes a distinct subgrid physics model, showing the robustness of our method. The PyTorch Geometric implementation of the GNN is publicly available on GitHub (https://github.com/PabloVD/HaloGraphNet).
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Lopez-Honorez, L., Mena, O., Palomares-Ruiz, S., & Villanueva-Domingo, P. (2017). Warm dark matter and the ionization history of the Universe. Phys. Rev. D, 96(10), 103539–14pp.
Abstract: In warm dark matter scenarios structure formation is suppressed on small scales with respect to the cold dark matter case, reducing the number of low-mass halos and the fraction of ionized gas at high redshifts and thus, delaying reionization. This has an impact on the ionization history of the Universe and measurements of the optical depth to reionization, of the evolution of the global fraction of ionized gas and of the thermal history of the intergalactic medium, can be used to set constraints on the mass of the dark matter particle. However, the suppression of the fraction of ionized medium in these scenarios can be partly compensated by varying other parameters, as the ionization efficiency or the minimum mass for which halos can host star-forming galaxies. Here we use different data sets regarding the ionization and thermal histories of the Universe and, taking into account the degeneracies from several astrophysical parameters, we obtain a lower bound on the mass of thermal warm dark matter candidates of m(X) > 1.3 keV, or m(s) > 5.5 keV for the case of sterile neutrinos nonresonantly produced in the early Universe, both at 90% confidence level.
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Witte, S., Villanueva-Domingo, P., Gariazzo, S., Mena, O., & Palomares-Ruiz, S. (2018). EDGES result versus CMB and low-redshift constraints on ionization histories. Phys. Rev. D, 97(10), 103533–8pp.
Abstract: We examine the results from the Experiment to Detect the Global Epoch of Reionization Signature (EDGES), which has recently claimed the detection of a strong absorption in the 21 cm hyperfine transition line of neutral hydrogen, at redshifts demarcating the early stages of star formation. More concretely, we study the compatibility of the shape of the EDGES absorption profile, centered at a redshift of z similar to 17.2, with measurements of the reionization optical depth, the Gunn-Peterson optical depth, and Lyman-alpha emission from star-forming galaxies, for a variety of possible reionization models within the standard ACDM framework (that is, a Universe with a cosmological constant. and cold dark matter CDM). When, conservatively, we only try to accommodate the location of the absorption dip, we identify a region in the parameter space of the astrophysical parameters that successfully explains all of the aforementioned observations. However, one of the most abnormal features of the EDGES measurement is the absorption amplitude, which is roughly a factor of 2 larger than the maximum allowed value in the ACDM framework. We point out that the simple considered astrophysical models that produce the largest absorption amplitudes are unable to explain the depth of the dip and of reproducing the observed shape of the absorption profile.
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