Journal Articles

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Browsing Journal Articles by Subject "0201 Astronomical and Space Sciences"

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    Enhancing the value of weather and climate services in society - identified gaps and needs as outcomes of the 1st WMO WWRP/SERA “Weather and Society” Conference
    (American Meteorological Society, 2023-02-14) Göber M; Isadora C; Hoffmann D; Mooney CJ; Rodriguez L; Becker N; Ebert EE; Fearnley C; Fundel VJ; Golding B; Jeurig J; Kelman I; Kox T; Magro F-A; Perrels A; Postigo JC; Potter SH; Robbins J; Rust H; Schoster D; Tan M; Taylor A; Williams H
    What: The Societal and Economics Research Application (SERA) Working Group of the World Meteorological Organization (WMO) World Weather Research Programme (WWRP) organized the first Weather and Society Conference, inviting the weather community to actively engage on critical themes to understand, analyze, and enhance the value of weather and climate services in society. The online conference ran over 2 weeks. Each session focused on a theme, ran for two hours, and included talks and discussion followed by a one-hour poster session. When: 28 February to 11 March 2022 Where: Online.
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    Measurement of the charge ratio of atmospheric muons with the CMS detector
    (ELSEVIER SCIENCE BV, 1/01/2010) Khachatryan V; Sirunyan AM; Tumasyan A; Adam W; Bergauer T; Dragicevic M; Erö J; Fabjan C; Friedl M; Frühwirth R; Ghete VM; Hammer J; Hänsel S; Hoch M; Hörmann N; Hrubec J; Jeitler M; Kasieczka G; Kiesenhofer W; Krammer M; Liko D; Mikulec I; Pernicka M; Rohringer H; Schöfbeck R; Strauss J; Taurok A; Teischinger F; Waltenberger W; Walzel G; Widl E; Wulz CE; Mossolov V; Shumeiko N; Suarez Gonzalez J; Benucci L; Ceard L; De Wolf EA; Hashemi M; Janssen X; Maes T; Mucibello L; Ochesanu S; Roland B; Rougny R; Selvaggi M; Van Haevermaet H; Van Mechelen P; Van Remortel N; Adler V; Beauceron S; Blyweert S; D'Hondt J; Devroede O; Kalogeropoulos A; Maes J; Maes M; Tavernier S; Van Doninck W; Van Mulders P; Villella I; Chabert EC; Charaf O; Clerbaux B; De Lentdecker G; Dero V; Gay APR; Hammad GH; Marage PE; Vander Velde C; Vanlaer P; Wickens J; Costantini S; Grunewald M; Klein B; Marinov A; Ryckbosch D; Thyssen F; Tytgat M; Vanelderen L; Verwilligen P; Walsh S; Zaganidis N; Basegmez S; Bruno G; Caudron J; De Favereau De Jeneret J; Delaere C; Demin P; Favart D; Giammanco A; Grégoire G; Hollar J; Lemaitre V; Militaru O; Ovyn S; Pagano D; Pin A; Piotrzkowski K; Quertenmont L
    We present a measurement of the ratio of positive to negative muon fluxes from cosmic ray interactions in the atmosphere, using data collected by the CMS detector both at ground level and in the underground experimental cavern at the CERN LHC. Muons were detected in the momentum range from 5 GeV/. c to 1 TeV/. c. The surface flux ratio is measured to be 1.2766±0.0032(stat.)±0.0032(syst.), independent of the muon momentum, below 100 GeV/. c. This is the most precise measurement to date. At higher momenta the data are consistent with an increase of the charge ratio, in agreement with cosmic ray shower models and compatible with previous measurements by deep-underground experiments. © 2010.
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    Transverse momentum and transverse momentum distributions in the MIT bag model
    (Elsevier, 10/03/2022) Signal A; Cao F-G
    The typical transverse momentum of a quark in the proton is a basic property of any QCD based model of nucleon structure. However, calculations in phenomenological models typically give rather small values of transverse momenta, which are difficult to reconcile with the larger values observed in high energy experiments such as Drell-Yan reactions and Semi-inclusive deep inelastic scattering. In this letter we calculate the leading twist transverse momentum dependent distribution functions (TMDs) using a generalization of the Adelaide group’s relativistic formalism that has previously given good fits to the parton distributions. This enables us to examine the kT dependence of the TMDs in detail, and determine typical widths of these distributions. These are found to be significantly larger than those of previous calculations. We then use TMD factorization in order to evolve these distributions up to experimental scales where we can compare with data on 〈kT 〉 and 〈k2 T 〉. Our distributions agree well with this data.