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Author Escrihuela, F.J.; Flores, L.J.; Miranda, O.G.; Rendon, J.
Title Global constraints on neutral-current generalized neutrino interactions Type Journal Article
Year 2021 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.
Volume 07 Issue 7 Pages (up) 061 - 26pp
Keywords Beyond Standard Model; Effective Field Theories; Neutrino Physics
Abstract We study generalized neutrino interactions (GNI) for several neutrino processes, including neutrinos from electron-positron collisions, neutrino-electron scattering, and neutrino deep inelastic scattering. We constrain scalar, pseudoscalar, and tensor new physics effective couplings, based on the standard model effective field theory at low energies. We have performed a global analysis for the different effective couplings. We also present the different individual constraints for each effective parameter (scalar, pseudoscalar, and tensor). Being a global analysis, we show robust results for the restrictions on the different GNI parameters and improve some of these bounds.
Address [Escrihuela, F. J.] Univ Valencia, Inst Fis Corpuscular CSIC, AHEP Grp, Parc Cient Paterna,C Catedrat Jose Beltran 2, E-46980 Paterna, Valencia, Spain, Email: franesfe@alumni.uv.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:000675383900009 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 4911
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Author Villaescusa-Navarro, F. et al; Villanueva-Domingo, P.
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 Astrophys. J. Suppl. Ser.
Volume 259 Issue 2 Pages (up) 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
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Author Vento, V.; Traini, M.
Title Scattering of charged particles off monopole-anti-monopole pairs Type Journal Article
Year 2020 Publication European Physical Journal C Abbreviated Journal Eur. Phys. J. C
Volume 80 Issue 1 Pages (up) 62 - 10pp
Keywords
Abstract The Large Hadron Collider is reaching energies never achieved before allowing the search for exotic particles in the TeV mass range. In a continuing effort to find monopoles we discuss the effect of the magnetic dipole field created by a pair of monopole-anti-monopole or monopolium on the successive bunches of charged particles in the beam at LHC.
Address [Vento, Vicente] Univ Valencia, CSIC, Dept Fis Teor, IFIC, E-46100 Valencia, Spain, Email: vicente.vento@uv.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 1434-6044 ISBN Medium
Area Expedition Conference
Notes WOS:000521222100001 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 4340
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Author ATLAS Collaboration (Aad, G. et al); Aparisi Pozo, J.A.; Bailey, A.J.; Cabrera Urban, S.; Castillo, F.L.; Castillo Gimenez, V.; Costa, M.J.; Escobar, C.; Estrada Pastor, O.; Ferrer, A.; Fiorini, L.; Fullana Torregrosa, E.; Fuster, J.; Garcia, C.; Garcia Navarro, J.E.; Gonzalez de la Hoz, S.; Gonzalvo Rodriguez, G.R.; Guerrero Rojas, J.G.R.; Higon-Rodriguez, E.; Lacasta, C.; Lozano Bahilo, J.J.; Madaffari, D.; Mamuzic, J.; Marti-Garcia, S.; Martinez Agullo, P.; Mitsou, V.A.; Moreno Llacer, M.; Poveda, J.; Rodriguez Bosca, S.; Ruiz-Martinez, A.; Salt, J.; Santra, A.; Sayago Galvan, I.; Soldevila, U.; Sanchez, J.; Valero, A.; Valls Ferrer, J.A.; Vos, M.
Title Search for new phenomena in final states with large jet multiplicities and missing transverse momentum using root s=13 TeV proton-proton collisions recorded by ATLAS in Run 2 of the LHC Type Journal Article
Year 2020 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.
Volume 10 Issue 10 Pages (up) 062 - 53pp
Keywords Hadron-Hadron scattering (experiments)
Abstract Results of a search for new particles decaying into eight or more jets and moderate missing transverse momentum are presented. The analysis uses 139 fb(-1) of proton-proton collision data at <mml:msqrt>s</mml:msqrt> = 13 TeV collected by the ATLAS experiment at the Large Hadron Collider between 2015 and 2018. The selection rejects events containing isolated electrons or muons, and makes requirements according to the number of b-tagged jets and the scalar sum of masses of large-radius jets. The search extends previous analyses both in using a larger dataset and by employing improved jet and missing transverse momentum reconstruction methods which more cleanly separate signal from background processes. No evidence for physics beyond the Standard Model is found. The results are interpreted in the context of supersymmetry-inspired simplified models, significantly extending the limits on the gluino mass in those models. In particular, limits on the gluino mass are set at 2 TeV when the lightest neutralino is nearly massless in a model assuming a two-step cascade decay via the lightest chargino and second-lightest neutralino.
Address [Banerjee, S.; Dang, N. P.; Duvnjak, D.; Jackson, P.; Oliver, J. L.; Petridis, A.; Qureshi, A.; Sharma, A. S.; White, M. J.] Univ Adelaide, Dept Phys, Adelaide, SA, Australia
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:000583331700001 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 4583
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Author Panes, B.; Eckner, C.; Hendriks, L.; Caron, S.; Dijkstra, K.; Johannesson, G.; Ruiz de Austri, R.; Zaharijas, G.
Title Identification of point sources in gamma rays using U-shaped convolutional neural networks and a data challenge Type Journal Article
Year 2021 Publication Astronomy & Astrophysics Abbreviated Journal Astron. Astrophys.
Volume 656 Issue Pages (up) A62 - 18pp
Keywords catalogs; gamma rays: general; astroparticle physics; methods: numerical; methods: data analysis; techniques: image processing
Abstract Context. At GeV energies, the sky is dominated by the interstellar emission from the Galaxy. With limited statistics and spatial resolution, accurately separating point sources is therefore challenging. Aims. Here we present the first application of deep learning based algorithms to automatically detect and classify point sources from gamma-ray data. For concreteness we refer to this approach as AutoSourceID. Methods. To detect point sources, we utilized U-shaped convolutional networks for image segmentation and k-means for source clustering and localization. We also explored the Centroid-Net algorithm, which is designed to find and count objects. Using two algorithms allows for a cross check of the results, while a combination of their results can be used to improve performance. The training data are based on 9.5 years of exposure from The Fermi Large Area Telescope (Fermi-LAT) and we used source properties of active galactic nuclei (AGNs) and pulsars (PSRs) from the fourth Fermi-LAT source catalog in addition to several models of background interstellar emission. The results of the localization algorithm are fed into a classification neural network that is trained to separate the three general source classes (AGNs, PSRs, and FAKE sources). Results. We compared our localization algorithms qualitatively with traditional methods and find them to have similar detection thresholds. We also demonstrate the robustness of our source localization algorithms to modifications in the interstellar emission models, which presents a clear advantage over traditional methods. The classification network is able to discriminate between the three classes with typical accuracy of similar to 70%, as long as balanced data sets are used in classification training. We published online our training data sets and analysis scripts and invite the community to join the data challenge aimed to improve the localization and classification of gamma-ray point sources.
Address [Panes, Boris] Pontificia Univ Catolica Chile, Ave Vicuna Mackenna 4860, Macul, Region Metropol, Chile, Email: bapanes@gmail.com
Corporate Author Thesis
Publisher Edp Sciences S A Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0004-6361 ISBN Medium
Area Expedition Conference
Notes WOS:000725877600001 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5053
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