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Author Centelles Chulia, S.; Cepedello, R.; Medina, O. url  doi
openurl 
  Title Absolute neutrino mass scale and dark matter stability from flavour symmetry Type Journal Article
  Year (down) 2022 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.  
  Volume 10 Issue 10 Pages 080 - 23pp  
  Keywords Discrete Symmetries; Flavour Symmetries; Neutrino Mixing; Particle Nature of Dark Matter  
  Abstract We explore a simple but extremely predictive extension of the scotogenic model. We promote the scotogenic symmetry Z(2) to the flavour non-Abelian symmetry sigma(81), which can also automatically protect dark matter stability. In addition, sigma(81) leads to striking predictions in the lepton sector: only Inverted Ordering is realised, the absolute neutrino mass scale is predicted to be m(lightest)approximate to 7.5x10(-4) eV and the Majorana phases are correlated in such a way that vertical bar m(ee)vertical bar approximate to 0.018 eV. The model also leads to a strong correlation between the solar mixing angle theta(12) and delta(CP), which may be falsified by the next generation of neutrino oscillation experiments. The setup is minimal in the sense that no additional symmetries or flavons are required.  
  Address [Chulia, Salvador Centelles] Max Planck Inst Kernphys, Saupfercheckweg 1, D-69117 Heidelberg, Germany, Email: chulia@mpi-hd.mpg.de;  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1029-8479 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000867661300002 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5387  
Permanent link to this record
 

 
Author Martinelli, M.; Scarcella, F.; Hogg, N.B.; Kavanagh, B.J.; Gaggero, D.; Fleury, P. url  doi
openurl 
  Title Dancing in the dark: detecting a population of distant primordial black holes Type Journal Article
  Year (down) 2022 Publication Journal of Cosmology and Astroparticle Physics Abbreviated Journal J. Cosmol. Astropart. Phys.  
  Volume 08 Issue 8 Pages 006 - 47pp  
  Keywords dark matter theory; gravitational waves / experiments; gravitational waves / sources; primordial black holes  
  Abstract Primordial black holes (PBHs) are compact objects proposed to have formed in the early Universe from the collapse of small-scale over-densities. Their existence may be detected from the observation of gravitational waves (GWs) emitted by PBH mergers, if the signals can be distinguished from those produced by the merging of astrophysical black holes. In this work, we forecast the capability of the Einstein Telescope, a proposed third-generation GW observatory, to identify and measure the abundance of a subdominant population of distant PBHs, using the difference in the redshift evolution of the merger rate of the two populations as our discriminant. We carefully model the merger rates and generate realistic mock catalogues of the luminosity distances and errors that would be obtained from GW signals observed by the Einstein Telescope. We use two independent statistical methods to analyse the mock data, finding that, with our more powerful, likelihood-based method, PBH abundances as small as fPBH approximate to 7 x 10(-6) ( fPBH approximate to 2 x 10(-6)) would be distinguishable from f(PBH) = 0 at the level of 3 sigma with a one year (ten year) observing run of the Einstein Telescope. Our mock data generation code, darksirens, is fast, easily extendable and publicly available on GitLab.  
  Address [Martinelli, Matteo] INAF Osservatorio Astron Roma, Via Frascati 33, I-00040 Rome, Italy, Email: matteo.martinelli@inaf.it;  
  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:000911612900001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5461  
Permanent link to this record
 

 
Author Aja, B. et al; Gimeno, B. url  doi
openurl 
  Title The Canfranc Axion Detection Experiment (CADEx): search for axions at 90 GHz with Kinetic Inductance Detectors Type Journal Article
  Year (down) 2022 Publication Journal of Cosmology And Astroparticle Physics Abbreviated Journal J. Cosmol. Astropart. Phys.  
  Volume 11 Issue 11 Pages 044 - 29pp  
  Keywords dark matter experiments; axions; dark matter detectors  
  Abstract We propose a novel experiment, the Canfranc Axion Detection Experiment (CADEx), to probe dark matter axions with masses in the range 330-460 μeV, within the W-band (80-110 GHz), an unexplored parameter space in the well-motivated dark matter window of Quantum ChromoDynamics (QCD) axions. The experimental design consists of a microwave resonant cavity haloscope in a high static magnetic field coupled to a highly sensitive detecting system based on Kinetic Inductance Detectors via optimized quasi-optics (horns and mirrors). The experiment is in preparation and will be installed in the dilution refrigerator of the Canfranc Underground Laboratory. Sensitivity forecasts for axion detection with CADEx, together with the potential of the experiment to search for dark photons, are presented.  
  Address [Aja, Beatriz; Artal, Eduardo; de la Fuente, Luisa; Pablo Pascual, Juan] Univ Cantabria, Dept Ingn Comunicac, Plaza Ciencia, Santander 39005, Spain, Email: ajab@unican.es;  
  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:000934034600003 Approved no  
  Is ISI yes International Collaboration no  
  Call Number IFIC @ pastor @ Serial 5478  
Permanent link to this record
 

 
Author Villanueva-Domingo, P.; Villaescusa-Navarro, F. url  doi
openurl 
  Title Removing Astrophysics in 21 cm Maps with Neural Networks Type Journal Article
  Year (down) 2021 Publication Astrophysical Journal Abbreviated Journal Astrophys. J.  
  Volume 907 Issue 1 Pages 44 - 14pp  
  Keywords Cosmology; Cold dark matter; Dark matter; Dark matter distribution; H I line emission; Intergalactic medium; Cosmological evolution; Convolutional neural networks; Large-scale structure of the universe  
  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.  
  Address [Villanueva-Domingo, Pablo] Univ Valencia, Inst Fis Corpuscular IFIC, CSIC, Apartado Correos 22085, E-46071 Valencia, Spain, Email: Pablo.Villanueva@ific.uv.es;  
  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:000612333400001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 4698  
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Author NEXT Collaboration (Kekic, M. et al); Benlloch-Rodriguez, J.M.; Carcel, S.; Carrion, J.V.; Diaz, J.; Felkai, R.; Lopez-March, N.; Martin-Albo, J.; Martinez, A.; Martinez-Lema, G.; Martinez-Vara, M.; Muñoz Vidal, J.; Novella, P.; Palmeiro, B.; Querol, M.; Renner, J.; Romo-Luque, C.; Sorel, M.; Uson, A.; Yahlali, N. url  doi
openurl 
  Title Demonstration of background rejection using deep convolutional neural networks in the NEXT experiment Type Journal Article
  Year (down) 2021 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.  
  Volume 01 Issue 1 Pages 189 - 22pp  
  Keywords Dark Matter and Double Beta Decay (experiments)  
  Abstract Convolutional neural networks (CNNs) are widely used state-of-the-art computer vision tools that are becoming increasingly popular in high-energy physics. In this paper, we attempt to understand the potential of CNNs for event classification in the NEXT experiment, which will search for neutrinoless double-beta decay in Xe-136. To do so, we demonstrate the usage of CNNs for the identification of electron-positron pair production events, which exhibit a topology similar to that of a neutrinoless double-beta decay event. These events were produced in the NEXT-White high-pressure xenon TPC using 2.6 MeV gamma rays from a Th-228 calibration source. We train a network on Monte Carlo-simulated events and show that, by applying on-the-fly data augmentation, the network can be made robust against differences between simulation and data. The use of CNNs offers significant improvement in signal efficiency and background rejection when compared to previous non-CNN-based analyses.  
  Address [Hauptman, J.; Nygren, D. R.] Iowa State Univ, Dept Phys & Astron, 12 Phys Hall, Ames, IA 50011 USA, Email: marija.kekic@usc.es  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1029-8479 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000616730800001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 4729  
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