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Author Viñals, S.; Nacher, E.; Tengblad, O.; Borge, M.J.G.; Briz, J.A.; Gad, A.; Munch, M.; Perea, A.
Title Calibration and response function of a compact silicon-detector set-up for charged-particle spectroscopy using GEANT4 Type Journal Article
Year 2021 Publication European Physical Journal A Abbreviated Journal Eur. Phys. J. A
Volume 57 Issue 2 Pages 49 - 9pp
Keywords
Abstract A complete methodology for detector calibration and energy-loss correction in charged-particle spectroscopy is presented. This has been applied to a compact set-up of four silicon detectors used for beta-delayed particle spectroscopy. The characterisation of the set-up was carried out using GEANT4 Monte Carlo simulations and standard alpha-calibration sources. The response function of the system was in this way accurately determined to be used for spectral unfolding.
Address (down) [Vinals, S.; Tengblad, O.; Borge, M. J. G.; Briz, J. A.; Perea, A.] CSIC, Inst Estruct Mat, E-28006 Madrid, Spain, Email: enrique.nacher@csic.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 1434-6001 ISBN Medium
Area Expedition Conference
Notes WOS:000615748600001 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 4710
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Author Villanueva-Domingo, P.; Villaescusa-Navarro, F.; Angles-Alcazar, D.; Genel, S.; Marinacci, F.; Spergel, D.N.; Hernquist, L.; Vogelsberger, M.; Dave, R.; Narayanan, D.
Title Inferring Halo Masses with Graph Neural Networks Type Journal Article
Year 2022 Publication Astrophysical Journal Abbreviated Journal Astrophys. J.
Volume 935 Issue 1 Pages 30 - 15pp
Keywords
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).
Address (down) [Villanueva-Domingo, Pablo] Univ Valencia, Inst Fis Corpuscular IFIC, CSIC, E-46980 Paterna, Spain, Email: pablo.villanueva.domingo@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 0004-637x ISBN Medium
Area Expedition Conference
Notes WOS:000838320900001 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5325
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Author Villanueva-Domingo, P.; Villaescusa-Navarro, F.
Title Removing Astrophysics in 21 cm Maps with Neural Networks Type Journal Article
Year 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 (down) [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 Villanueva-Domingo, P.; Ichiki, K.
Title 21 cm forest constraints on primordial black holes Type Journal Article
Year 2023 Publication Publications of the Astronomical Society of Japan Abbreviated Journal Publ. Astron. Soc. Jpn.
Volume 75 Issue SP1 Pages S33-S49
Keywords dark matter; radio lines: ISM
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.
Address (down) [Villanueva-Domingo, Pablo] Univ Valencia, Inst Fis Corpuscular IFIC, CSIC, Apartado Correos 22085, E-46071 Valencia, Spain, Email: ichiki@a.phys.nagoya-u.ac.jp
Corporate Author Thesis
Publisher Oxford Univ Press Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0004-6264 ISBN Medium
Area Expedition Conference
Notes WOS:000768441900001 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5168
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Author Villanueva-Domingo, P.; Villaescusa-Navarro, F.; Genel, S.; Angles-Alcazar, D.; Hernquist, L.; Marinacci, F.; Spergel, D.N.; Vogelsberger, M.; Narayanan, D.
Title Weighing the Milky Way and Andromeda galaxies with artificial intelligence Type Journal Article
Year 2023 Publication Physical Review D Abbreviated Journal Phys. Rev. D
Volume 107 Issue 10 Pages 103003 - 8pp
Keywords
Abstract We present new constraints on the masses of the halos hosting the Milky Way and Andromeda galaxies derived using graph neural networks. Our models, trained on 2,000 state-of-the-art hydrodynamic simulations of the CAMELS project, only make use of the positions, velocities and stellar masses of the galaxies belonging to the halos, and are able to perform likelihood-free inference on halo masses while accounting for both cosmological and astrophysical uncertainties. Our constraints are in agreement with estimates from other traditional methods, within our derived posterior standard deviation.
Address (down) [Villanueva-Domingo, Pablo; Narayanan, Desika] Univ Valencia, CSIC, Inst Fis Corpuscular IFIC, E-46980 Paterna, Spain, Email: pablo.villanueva.domingo@gmail.com;
Corporate Author Thesis
Publisher Amer Physical Soc Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2470-0010 ISBN Medium
Area Expedition Conference
Notes WOS:000988340900001 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5539
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