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Author Bennett, J.J.; Buldgen, G.; de Salas, P.F.; Drewes, M.; Gariazzo, S.; Pastor, S.; Wong, Y.Y.Y.
Title Towards a precision calculation of the effective number of neutrinos N-eff in the Standard Model. Part II. Neutrino decoupling in the presence of flavour oscillations and finite-temperature QED Type Journal Article
Year 2021 Publication Journal of Cosmology and Astroparticle Physics Abbreviated Journal J. Cosmol. Astropart. Phys.
Volume 04 Issue 4 Pages 073 - 33pp
Keywords cosmological neutrinos; neutrino properties; particle physics – cosmology connection; physics of the early universe
Abstract We present in this work a new calculation of the standard-model benchmark value for the effective number of neutrinos, N-eff(SM), that quantifies the cosmological neutrinoto-photon energy densities. The calculation takes into account neutrino flavour oscillations, finite-temperature effects in the quantum electrodynamics plasma to O(e(3)), where e is the elementary electric charge, and a full evaluation of the neutrino-neutrino collision integral. We provide furthermore a detailed assessment of the uncertainties in the benchmark N(eff)(SM )value, through testing the value's dependence on (i) optional approximate modelling of the weak collision integrals, (ii) measurement errors in the physical parameters of the weak sector, and (iii) numerical convergence, particularly in relation to momentum discretisation. Our new, recommended standard-model benchmark is N-eff(SM) 3.0440 +/- 0.0002, where the nominal uncertainty is attributed predominantly to errors incurred in the numerical solution procedure (vertical bar delta N-eff vertical bar similar to 10(-4)), augmented by measurement errors in the solar mixing angle sin(2) theta(12) (vertical bar delta N-eff vertical bar similar to 10(-4)).
Address [Bennett, Jack J.; Wong, Yvonne Y. Y.] Univ New South Wales, Sch Phys, Sydney Consortium Particle Phys & Cosmol, Sydney, NSW 2052, Australia, Email: j.j.bennett@unsw.edu.au;
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:000647827600001 Approved no
Is ISI yes International Collaboration (up) yes
Call Number IFIC @ pastor @ Serial 4827
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Author Salesa Greus, F.; Sanchez Losa, A.
Title Multimessenger Astronomy with Neutrinos Type Journal Article
Year 2021 Publication Universe Abbreviated Journal Universe
Volume 7 Issue 11 Pages 397 - 11pp
Keywords multimessenger astronomy; astroparticle physics; neutrinos
Abstract Multimessenger astronomy is arguably the branch of the astroparticle physics field that has seen the most significant developments in recent years. In this manuscript, we will review the state-of-the-art, the recent observations, and the prospects and challenges for the near future. We will give special emphasis to the observation carried out with neutrino telescopes.
Address [Salesa Greus, Francisco; Sanchez Losa, Agustin] Univ Valencia, CSIC, IFIC Inst Fis Corpuscular, C Catedratico Jose Beltran 2, E-46980 Paterna, Spain, Email: sagreus@ific.uv.es;
Corporate Author Thesis
Publisher Mdpi Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes WOS:000724957500001 Approved no
Is ISI yes International Collaboration (up) yes
Call Number IFIC @ pastor @ Serial 5036
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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 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 (up) yes
Call Number IFIC @ pastor @ Serial 5053
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Author AbdusSalam, S.S. et al; Eberhardt, O.
Title Simple and statistically sound recommendations for analysing physical theories Type Journal Article
Year 2022 Publication Reports on Progress in Physics Abbreviated Journal Rep. Prog. Phys.
Volume 85 Issue 5 Pages 052201 - 11pp
Keywords particle physics; statistics; methodology
Abstract Physical theories that depend on many parameters or are tested against data from many different experiments pose unique challenges to statistical inference. Many models in particle physics, astrophysics and cosmology fall into one or both of these categories. These issues are often sidestepped with statistically unsound ad hoc methods, involving intersection of parameter intervals estimated by multiple experiments, and random or grid sampling of model parameters. Whilst these methods are easy to apply, they exhibit pathologies even in low-dimensional parameter spaces, and quickly become problematic to use and interpret in higher dimensions. In this article we give clear guidance for going beyond these procedures, suggesting where possible simple methods for performing statistically sound inference, and recommendations of readily-available software tools and standards that can assist in doing so. Our aim is to provide any physicists lacking comprehensive statistical training with recommendations for reaching correct scientific conclusions, with only a modest increase in analysis burden. Our examples can be reproduced with the code publicly available at Zenodo.
Address [AbdusSalam, Shehu S.; Fowlie, Andrew] Shahid Beheshti Univ, Dept Phys, Tehran, Iran, Email: andrew.j.fowlie@njnu.edu.cn
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 0034-4885 ISBN Medium
Area Expedition Conference
Notes WOS:000791574900001 Approved no
Is ISI yes International Collaboration (up) yes
Call Number IFIC @ pastor @ Serial 5221
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Author Super-Kamiokande Collaboration (Abe, K. et al); Molina Sedgwick, S.
Title Neutron tagging following atmospheric neutrino events in a water Cherenkov detector Type Journal Article
Year 2022 Publication Journal of Instrumentation Abbreviated Journal J. Instrum.
Volume 17 Issue 10 Pages P10029 - 41pp
Keywords Particle identification methods; Cherenkov detectors; Neutrino detectors; Large detector systems for particle and astroparticle physics
Abstract We present the development of neutron-tagging techniques in Super-Kamiokande IV using a neural network analysis. The detection efficiency of neutron capture on hydrogen is estimated to be 26%, with a mis-tag rate of 0.016 per neutrino event. The uncertainty of the tagging efficiency is estimated to be 9.0%. Measurement of the tagging efficiency with data from an Americium-Beryllium calibration agrees with this value within 10%. The tagging procedure was performed on 3,244.4 days of SK-IV atmospheric neutrino data, identifying 18,091 neutrons in 26,473 neutrino events. The fitted neutron capture lifetime was measured as 218 +/- 9 μs.
Address [Abe, K.; Haga, Y.; Hayato, Y.; Hiraide, K.; Ieki, K.; Ikeda, M.; Imaizumi, S.; Iyogi, K.; Kameda, J.; Kanemura, Y.; Kataoka, Y.; Kato, Y.; Kishimoto, Y.; Miki, S.; Mine, S.; Miura, M.; Mochizuki, T.; Moriyama, S.; Nagao, Y.; Nakahata, M.; Nakajima, T.; Nakano, Y.; Nakayama, S.; Okada, T.; Okamoto, K.; Orii, A.; Sato, K.; Sekiya, H.; Shiozawa, M.; Sonoda, Y.; Suzuki, Y.; Takeda, A.; Takemoto, Y.; Takenaka, A.; Tanaka, H.; Tasaka, S.; Tomura, T.; Ueno, K.; Watanabe, S.; Yano, T.; Yokozawa, T.] Univ Tokyo, Inst Cosm Ray Res, Kamioka Observ, Gifu, Akita 5061205, Japan, Email: hayato@icrr.u-tokyo.ac.jp
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 1748-0221 ISBN Medium
Area Expedition Conference
Notes WOS:000898723700008 Approved no
Is ISI yes International Collaboration (up) yes
Call Number IFIC @ pastor @ Serial 5441
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