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Author Bernal, N.; Munoz-Albornoz, V.; Palomares-Ruiz, S.; Villanueva-Domingo, P. url  doi
openurl 
  Title Current and future neutrino limits on the abundance of primordial black holes Type Journal Article
  Year 2022 Publication Journal of Cosmology and Astroparticle Physics Abbreviated Journal (down) J. Cosmol. Astropart. Phys.  
  Volume 10 Issue 10 Pages 068 - 38pp  
  Keywords neutrino detectors; primordial black holes  
  Abstract Primordial black holes (PBHs) formed in the early Universe are sources of neutrinos emitted via Hawking radiation. Such astrophysical neutrinos could be detected at Earth and constraints on the abundance of comet-mass PBHs could be derived from the null observation of this neutrino flux. Here, we consider non-rotating PBHs and improve constraints using Super-Kamiokande neutrino data, as well as we perform forecasts for next-generation neutrino (Hyper-Kamiokande, JUNO, DUNE) and dark matter (DARWIN, ARGO) detectors, which we compare. For PBHs less massive than " few x 1014 g, PBHs would have already evaporated by now, whereas more massive PBHs would still be present and would constitute a fraction of the dark matter of the Universe. We consider monochromatic and extended (log-normal) mass distributions, and a PBH mass range spanning from 1012 g to ti 1016 g. Finally, we also compare our results with previous ones in the literature.  
  Address [Bernal, Nicolas] New York Univ Abu Dhabi, POB 129188, Abu Dhabi, U Arab Emirates, Email: nicolas.bernal@uan.edu.co;  
  Corporate Author Thesis  
  Publisher IOP Publishing Ltd Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1475-7516 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000882783900003 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5412  
Permanent link to this record
 

 
Author Villanueva-Domingo, P.; Mena, O.; Palomares-Ruiz, S. url  doi
openurl 
  Title A Brief Review on Primordial Black Holes as Dark Matter Type Journal Article
  Year 2021 Publication Frontiers in Astronomy and Space Sciences Abbreviated Journal (down) Front. Astron. Space Sci.  
  Volume 8 Issue Pages 681084 - 10pp  
  Keywords primordial black holes; dark matter; cosmology; accretion; 21 cm cosmology; gravitational waves; cosmic microwave background; microlensing  
  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.  
  Address [Villanueva-Domingo, Pablo; Mena, Olga; Palomares-Ruiz, Sergio] CSIC Univ Valencia, Inst Fis Corpuscular IFIC, Paterna, Spain, Email: pablo.villanueva.domingo@gmail.com  
  Corporate Author Thesis  
  Publisher Frontiers Media Sa Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2296-987x ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000660081700001 Approved no  
  Is ISI yes International Collaboration no  
  Call Number IFIC @ pastor @ Serial 4852  
Permanent link to this record
 

 
Author Villaescusa-Navarro, F. et al; Villanueva-Domingo, P. url  doi
openurl 
  Title The CAMELS Multifield Data Set: Learning the Universe's Fundamental Parameters with Artificial Intelligence Type Journal Article
  Year 2022 Publication Astrophysical Journal Supplement Series Abbreviated Journal (down) Astrophys. J. Suppl. Ser.  
  Volume 259 Issue 2 Pages 61 - 14pp  
  Keywords  
  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.  
  Address [Villaescusa-Navarro, Francisco; Nicola, Andrina; Spergel, David N.; Matilla, Jose Manuel Zorrilla; Shao, Helen] Princeton Univ, Dept Astrophys Sci, Peyton Hall, Princeton, NJ 08544 USA, Email: villaescusa.francisco@gmail.com  
  Corporate Author Thesis  
  Publisher IOP Publishing Ltd Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0067-0049 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000780035300001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5194  
Permanent link to this record
 

 
Author Villaescusa-Navarro, F. et al; Villanueva-Domingo, P. url  doi
openurl 
  Title The CAMELS Project: Public Data Release Type Journal Article
  Year 2023 Publication Astrophysical Journal Supplement Series Abbreviated Journal (down) Astrophys. J. Suppl. Ser.  
  Volume 265 Issue 2 Pages 54 - 14pp  
  Keywords Cosmology; Hydrodynamical simulations; Astrostatistics; Galaxy formation  
  Abstract The Cosmology and Astrophysics with Machine Learning Simulations (CAMELS) project was developed to combine cosmology with astrophysics through thousands of cosmological hydrodynamic simulations and machine learning. CAMELS contains 4233 cosmological simulations, 2049 N-body simulations, and 2184 state-of-the-art hydrodynamic simulations that sample a vast volume in parameter space. In this paper, we present the CAMELS public data release, describing the characteristics of the CAMELS simulations and a variety of data products generated from them, including halo, subhalo, galaxy, and void catalogs, power spectra, bispectra, Lya spectra, probability distribution functions, halo radial profiles, and X-rays photon lists. We also release over 1000 catalogs that contain billions of galaxies from CAMELS-SAM: a large collection of N-body simulations that have been combined with the Santa Cruz semianalytic model. We release all the data, comprising more than 350 terabytes and containing 143,922 snapshots, millions of halos, galaxies, and summary statistics. We provide further technical details on how to access, download, read, and process the data at .  
  Address [Villaescusa-Navarro, Francisco; Genel, Shy; Angles-Alcazar, Daniel; Hassan, Sultan; Pisani, Alice; Wong, Kaze W. K.; Coulton, William R.; Steinwandel, Ulrich P.; Spergel, David N.; Burkhart, Blakesley; Wandelt, Benjamin; Somerville, Rachel S.; Bryan, Greg L.; Li, Yin] Flatiron Inst, Ctr Computat Astrophys, 162 5th Ave, New York, NY 10010 USA, Email: camel.simulations@gmail.com  
  Corporate Author Thesis  
  Publisher IOP Publishing Ltd Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0067-0049 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000964876300001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5525  
Permanent link to this record
 

 
Author Villanueva-Domingo, P.; Gnedin, N.Y.; Mena, O. url  doi
openurl 
  Title Warm Dark Matter and Cosmic Reionization Type Journal Article
  Year 2018 Publication Astrophysical Journal Abbreviated Journal (down) Astrophys. J.  
  Volume 852 Issue 2 Pages 139 - 7pp  
  Keywords cosmology: theory; galaxies: formation; intergalactic medium; large-scale structure of universe; methods: numerical  
  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.  
  Address [Villanueva-Domingo, Pablo; Mena, Olga] Univ Valencia, CSIC, Inst Fis Corpuscular IFIC, Apartado Correos 22085, E-46071 Valencia, Spain, Email: gnedin@fnal.gov  
  Corporate Author Thesis  
  Publisher Iop Publishing Ltd Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0004-637x ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000422865600009 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 3455  
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